Intro

Dataset from the publication "Lithium-ion battery degradation: comprehensive cycle ageing data and analysis for commercial 21700 cells", DOI: https://doi.org/10.1016/j.jpowsour.2024.234185

Full details of the study can be found in the publication, including thorough descriptions of the experimental methods and structure. A basic desciption of the experimental procedure and data structure is included here for ease of use.

Commercial 21700 cylindrical cells (LG M50T, LG GBM50T2170) were cycle aged under 3 different temperatures [10, 25, 40] °C and 4 different SoC ranges [0-30, 70-85, 85-100, 0-100]%, as well as a further [0-100]% SoC range experiment which utilised a drive-cycle discharge instead of constant-current. The same C-rates (0.3C / 1 C, for charge / discharge) were used in all tests; multiple cells were tested under each condition. These are listed in the table below.

Experiment

SOC Window

Cycles per ageing set

Current

Temperature

Number of Cells

1

0-30%

257

0.3C / 1D

10°C

3

25°C

3

40°C

3

2,2

70-85%

515

0.3C / 1D

10°C

2

25°C

2

40°C

2

3

85-100%

515

0.3C / 1D

10°C

3

25°C

3

40°C

3

4

0-100% (drive-cycle)

78

0.3C / noisy D

10°C

3

25°C

2

40°C

3

5

0-100%

78

0.3C / 1D

10°C

3

25°C

2

40°C

3

Cells were base-cooled at set temperatures using bespoke test rigs (see our linked publications for details; the supporting information file contains detailed descriptions and photographs). Cells were subject to break-in cycles prior to beginning of life (BoL) performance tests using the ‘Reference Performance Test’ (RPT) procedures. They were then alternately subject to ageing sets and RPTs until the end of testing. Full details of each of these procedures are described in the linked publication.

The data contained in this repository is then described in the Data section below. This includes a description of the folder structure and naming conventions, file formats, and data analysis methods used for the ‘Processed Data’ which has been calculated from the raw data.

An 'experimental_metadata' .xlsx file is included to aid parsing of data. A jupyter notebook has also been included to demonstate how to access some of the data.

Data

Data are organised according to their parent ‘Experiment’, as defined above, with a folder for each. Within each Experiment folder, there are 3 subfolders: ‘Summary Data’, ‘Processed Timeseries Data’, and ‘Raw Data’.

Summary Data

This folder contains data which has been extracted by processing the raw data in the ‘Degradation Cycling’ and ‘Performance Checks’ folders. In most cases, the data you are looking for will be stored here.

It contains:

Performance Summary

A summary file for each cell which details key ageing metrics such as number of ageing cycles, charge throughput, cell capacity, resistance, and degradation mode analysis results. Each row of data corresponds to a different SoH.

Degradation Mode Analysis (DMA) was also performed on the C/10 discharge data at each RPT. This analysis uses an optimisation function to determine the capacities and offset of the positive and negative electrodes by calculating a full cell voltage vs capacity curve using 1/2 cell data and comparing against the experimentally measured voltage vs capacity data from the C/10 discharge. See our ACS publication for more details.

Data includes:

· Ageing Set: numbered 0 (BoL) to x, where x is the number of ageing sets the cell has been subject to.

· Ageing Cycles: number of ageing cycles the cell has been subject to. *this is not equivalent full cycles.

· Ageing Set Start Date/ End date: The date that each ageing set began/ ended.

· Days of degradation: Number of days between the date of the first ageing set beginning and the current ageing set ending.

· Age set average temperature: average recorded surface temperature of the cell during cycle ageing. Temperature was recorded approximately 1/2 way up the length of the cell (i.e. between positive and negative caps).

· Charge throughput: total accumulated charge recorded during all cycles during ageing (i.e. sum of charge and discharge). This is the cumulative total since BoL (not including RPTs, and not including break-in cycles).

· Energy throughput: as with "charge throughput", but for energy.

· C/10 Capacity: the capacity recorded during the C/10 discharge test of each RPT.

· C/2 Capacity: the capacity recorded during the C/2 discharge test of each even-numbered RPT.

· 0.1s Resistance: The resistance calculated from the 25-pulse GITT test of each even-numbered RPT. This value is taken from the 12th pulse of the procedure (which corresponds to ~52% SoC at BoL). The resistance is calculated by dividing the voltage drop by the current at a timecale of 0.1 seconds after the current pulse is applied (the fastest timescale possible under the 10 Hz recording condition).

· Fitting parameters: output from the DMA optimisation function; 5 parameters which detail the upper/lower SoCs of each electrode, and the capacity fraction of graphite in the negative electrode.

· Capacity and offset data: calculated based on the fitting parameters above alongside the measured C/10 discharge capacity.

· DM data: Quantities of LLI, LAM-PE, LAM-NE, LAM-NE-Gr, and LAM-NE-Si calculated from the change in capacities/offset of each electrode since BoL.

· RMSE data: the root mean squared error of the optimisation function calculated from the residual between the measured and simulated voltage vs capacity profiles.

Ageing Sets Summary

Data from the ageing cycles, summarised on an average per cycle and an average per ageing set basis. Metrics include mean/ max/ min temperatures, voltages etc.

Processed Timeseries data

Timeseries data (voltage, current, temperature, etc.) from each subtest (pOCV, GITT, etc.) of the RPTs, all grouped by subtest-type and by cell ID.

Contains the same data as in the ‘Performance Checks’ subfolder of the 'Raw Data' folder, but has been processed to slice into relevant subtests from the RPT procedure and includes only limited variables (time, voltage, current, charge, temperature). These are all saved as .csv files. In general this data will be easier to access than the raw data, but perhaps not as rich.

Raw Data

These are the raw data from the performance checks and from the degradation cycles themselves. The data from here has already been processed by me to get values of ‘energy throughput’, ‘charge throughput’, ‘average ageing temperature’, etc., which are all saved in the ‘Summary Data’ folder as described in the relevant section above.

The data in the ‘Degradation Cycling’ folder are organised by ageing set (where an ageing set is a defined number of ageing cycles, as described in the paper). In theory, each cell should have one datafile in each ageing set subfolder. However, due to experimental issues, tests can sometimes be interrupted midway though, requiring the test to be subsequently resumed. In this case, there may be multiple datafiles for each cell in a given ageing set; during analysis, these should be concatenated according to the descriptor in the filename (e.g., ‘cycling7’ + ‘cycling7 (part 2)').

Similarly, the unprocessed raw data from the performance checks (i.e. RPTs) is stored in the 'Performance Checks' folder, and structured in the same way.

The raw data are saved in the .mpr format produced by the Biologic battery cycler. This is a binary format which is storage-efficient but can be more difficult to process for analysis purposes. We have therefore also exported the data into .txt files (called .mpt) for the performance checks (RPTs) which make analysis easier. However, the exported .mpt files could not be included for the degradation cycling files due to their larger size. If you require access these degradation cycle data, the .mpr binary file can be parsed using the Galvani package in python, or you can use Biologic’s (proprietary) BT-Lab software to export the data into .txt files.

File Naming Convention

The raw datafiles are named with a standard format. This is:

    NDK - LG M50 deg - exp 1 - rig 1 - 10degC - cell A - RPT1_01_MB_CB1

    {NDK - LG M50 deg} - {exp 1} – {rig 1} – {10degC} – {cell A} – {RPT1}_{01}_{MB}_{CB1}

{Standard prefix} – {experiment number} – {ID of test rig} – {control temperature} – {Cell ID} – {RPT number or aging cycle number}_{step number for the characterisation procedure (see above)}_{experimental technique name (will always be “MB”)}_{battery cycler channel ID used (always the same for a particular cell/experiment)}

The Data Center Lithium-ion Battery market is experiencing robust growth, projected to reach a value of $506 million in 2025 and maintain a Compound Annual Growth Rate (CAGR) of 9.8% from 2025 to 2033. This expansion is driven primarily by the increasing demand for reliable and efficient power backup solutions in data centers, fueled by the exponential growth of cloud computing, big data analytics, and the Internet of Things (IoT). The rising concerns regarding power outages and their potential impact on business continuity are further strengthening market adoption. Key trends shaping the market include the increasing adoption of higher energy density battery technologies, the development of advanced battery management systems (BMS) for improved safety and performance, and a growing preference for modular and scalable battery solutions that can easily integrate with existing data center infrastructure. Major players such as Huawei, Eaton, Schneider Electric, Mitsubishi Electric Power Products Inc, ABB, and Narada are driving innovation and competition, focusing on product differentiation through enhanced performance, longer lifespan, and improved sustainability features. Despite the positive growth trajectory, certain restraints remain. The high initial investment costs associated with lithium-ion battery systems and concerns regarding battery safety and lifecycle management pose challenges to market penetration. However, ongoing technological advancements, coupled with government initiatives promoting renewable energy and energy efficiency, are expected to mitigate these limitations and continue to propel market growth. The segmentation of the market, although not explicitly provided, is likely categorized by battery chemistry (e.g., LiFePO4, NMC), capacity, form factor (rack-mounted, modular), and application (UPS, emergency power). The regional distribution of the market is expected to vary, with North America and Europe representing significant market shares initially, followed by growth in Asia-Pacific driven by the booming data center infrastructure development in regions like China and India.

Dataset Overview

This dataset provides a comprehensive view of the aging process of lithium-ion batteries, facilitating the estimation of their Remaining Useful Life (RUL). Originally sourced from NASA's open repository, the dataset has undergone meticulous preprocessing to enhance its analytical utility. The data is presented in a user-friendly CSV format after extracting relevant features from the original .mat files.

Key Features of the Dataset

1. Battery Performance Metrics:

   • Capacity: Measured over time to assess degradation.
   • Internal Resistance (Re): Represents the electrical resistance of the battery.
   • Charge Transfer Resistance (Rct): Indicates charge movement efficiency.

2. Environmental Conditions:

   • Ambient Temperature: External temperature affecting battery performance.

3. Identification Attributes:

   • Battery ID: Unique identifier for each battery tested.
   • Test ID: Links specific test conditions to outcomes.
   • UID & Filename: Traceable dataset references.

4. Processed Data:

   • Missing values have been addressed.
   • Columns irrelevant to RUL estimation have been removed.
   • Skewness in the data has been corrected for statistical accuracy.

5. Labels:

   • Degradation States: Categorized into intervals for easier interpretation.
   • Ranges include operational and failure states.

Potential Applications

1. Battery Health Monitoring:

   • Predict battery failure timelines.
   • Enhance battery maintenance strategies.

2. Data Science and Machine Learning:

   • Model development for RUL prediction.
   • Feature engineering for predictive analysis.

3. Research and Development:

   • Improve battery design.
   • Study the impact of environmental and operational conditions on battery life.

Technical Details

• File Format: CSV
• Size: ~625.02 kB
• Columns: 9
• Data Points: Multiple observations across various tests.

Tags

• Keywords: Lithium-ion batteries, RUL, Battery Aging, Machine Learning, Data Analysis, Predictive Maintenance.

License

• Apache 2.0: Permits academic and commercial use.

Usage Instructions

1. Import the dataset into your data analysis tools (e.g., Python, R, MATLAB).
2. Explore features to understand correlations and dependencies.
3. Use machine learning models for RUL prediction.

Provenance

The dataset was retrieved from NASA's publicly available data repositories. It has been preprocessed to align with research and industrial standards for usability in analytical tasks.

Call to Action

Leverage this dataset to enhance your understanding of lithium-ion battery degradation and build models that could revolutionize energy storage solutions.

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Lithium-Ion Battery Management Systems For Vehicles Market Size 2025-2029

The lithium-ion battery management systems (BMS) for vehicles market size is forecast to increase by USD 4.24 billion at a CAGR of 18.6% between 2024 and 2029.

The market is experiencing significant growth, driven primarily by the expanding electric vehicles (EV) sector. The increasing adoption of EVs due to environmental concerns and government incentives is leading to a surge in demand for advanced BMS solutions. Another key trend in the market is the emergence of cloud-based BMS services, enabling real-time monitoring and remote diagnostics, enhancing vehicle performance and safety. However, the market is not without challenges, with the fluctuating cost of raw materials, such as lithium-ion and cobalt, posing significant risks to profitability.
To capitalize on the market opportunities and navigate these challenges effectively, companies must focus on innovation, cost reduction, and strategic partnerships. By investing in research and development, optimizing supply chain management, and collaborating with industry leaders, organizations can differentiate themselves and stay competitive in the dynamic and rapidly evolving Lithium-Ion BMS for Vehicles market.

What will be the Size of the Lithium-Ion Battery Management Systems (BMS) For Vehicles Market during the forecast period?

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The Lithium-ion Battery Management Systems (BMS) market for vehicles is experiencing significant growth due to the increasing adoption of electric vehicles (EVs) and the demand for improved fuel efficiency. BMS plays a crucial role in ensuring the optimal performance and safety of EV batteries. Key features of BMS include battery capacity management, battery control unit, battery pack monitoring, battery data acquisition, and battery performance optimization. Advanced functions such as battery modeling, charging station management, battery telematics, and battery data analysis are also gaining popularity. Battery cell chemistry, including lithium-iron-phosphate and nickel-manganese-cobalt, significantly influences battery performance. In the telecommunications sector, lithium-ion BMS find applications in data centers, cell towers, and backup power systems, providing reliable energy storage and management.
BMS also facilitates battery aging management, battery sensing, and battery testing to ensure safety and prolong battery life. Electric powertrains and connected vehicles require sophisticated BMS for efficient energy management and real-time monitoring. Battery swapping and battery simulation are emerging trends in the market. Battery degradation and battery lifecycle management are critical challenges that BMS addresses through advanced analytics and optimization techniques. Solid-state batteries and battery protection circuitry are future technologies that will further enhance battery performance and safety. Battery analytics and calibration are essential for maintaining optimal battery efficiency and ensuring compliance with safety standards.
Overall, the Lithium-ion BMS market for vehicles is a dynamic and innovative space, driven by advancements in battery technology and the growing demand for sustainable transportation solutions.

How is this Lithium-Ion Battery Management Systems (BMS) For Vehicles Industry segmented?

The lithium-ion battery management systems (BMS) for vehicles industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.

Type

  Centralized BMS
  Distributed BMS
  Modular BMS


Product Type

  Lithium-iron phosphate
  Lithium-ion batteries
  Lithium-cobalt oxide
  Lithium-manganese oxide
  Others


Application

  Battery electric vehicles
  Hybrid electric vehicles
  Others


Geography

  North America

    US
    Canada


  Europe

    France
    Germany
    UK


  APAC

    Australia
    China
    India
    Japan
    South Korea


  Rest of World (ROW)

By Type Insights

The centralized BMS segment is estimated to witness significant growth during the forecast period. The lithium-ion battery management system (BMS) market for vehicles is witnessing significant growth due to the increasing adoption of electric and hybrid vehicles, as well as renewable energy storage systems. Centralized BMS, which utilizes a single control unit to manage all battery cells, is gaining popularity for its cost-effectiveness and streamlined communication and management capabilities. This architecture is particularly beneficial for electric vehicles and energy storage systems, addressing concerns such as battery safety, thermal management, voltage monitoring, and charge/discharge rate. This segment comprises e-scooters, e-bikes, e-motorcycles, electric cars, elect

A tremendous commitment of resources is needed to acquire, understand and apply battery data in terms of performance and aging behavior. There are many state of performance (SOP) and state of health (SOH) metrics that are useful to guide alignment of batteries to end-use, yet how these metrics are measured or extracted can make the difference between usable, valuable datasets versus data that lacks the necessary integrity to meet baseline confidence levels for SOP/SOH quantification. This work will speak to 1) types of data that support SOP and SOH evaluations on mechanistic terms, 2) measurement conditions needed to assure high data integrity, 3) equipment limitations that can compromise data high fidelity, and 4) the impact of cell polarization on data quality. A common goal in battery research and field use is to work from a data platform that supports economical paths of data capture while minimizing down-time for battery diagnostics. An ideal situation would be to utilize data obtained during normal daily use (“pulses or cycles of convenience”) without stopping the daily duty cycles to perform dedicated SOP/SOH diagnostic routines. However, difficulties arise in trying to make use of daily duty cycle data (denoted as cycle-by-cycle, CBC) that underscores the need for standardization of conditions: temperature and duty cycles can vary over the course of a day and throughout a week, month and year; polarization can develop within an immediate cycle and throughout successive cycles as a hysteresis. If CBC data is envisioned as a data source to determine performance and aging trends, it should be recognized that polarization is a frequent consequence of CBC and thus makes it difficult to separate reversible and irreversible components to metrics such as capacity loss and resistance increase over aging. Since CBC conditions can have a major impact on data usability, we will devote part of this paper to CBC data conditioning and management. Differential analyses will also be discussed as a means to detect changing trends in data quality. Our target cell chemistries will be lithium-ion types NMC/graphite and LMO/LTO.

The global data center energy storage battery market is anticipated to reach a value of USD 10.9 billion by 2030, expanding at a CAGR of 15.2% over the forecast period. This growth is driven by the increasing need for reliable and efficient power backup in data centers to ensure business continuity, reduce downtime, and minimize data loss. Additionally, the growing adoption of cloud computing, big data, and the Internet of Things (IoT) is fueling the demand for data centers, which is in turn driving the demand for energy storage batteries. The market is segmented by application into internet industry, finance and insurance, manufacture, government, and others. The internet industry is expected to hold the largest market share due to the high concentration of data centers in this sector. By type, the market is divided into lead-acid batteries, lithium-ion batteries, and others. Lithium-ion batteries are expected to dominate the market due to their higher energy density, longer lifespan, and lower maintenance costs. Regionally, North America is expected to account for the largest market share due to the presence of major data center operators and a high adoption rate of advanced technologies.

Battery Analytics for MHE Market Outlook

According to our latest research, the global Battery Analytics for MHE (Material Handling Equipment) market size stands at USD 1.62 billion in 2024, with a robust Compound Annual Growth Rate (CAGR) of 18.7% projected from 2025 to 2033. By 2033, the market is anticipated to reach USD 8.37 billion, reflecting the rapid adoption of advanced battery analytics solutions across key industries. This substantial growth is primarily driven by the increasing demand for operational efficiency, cost reduction, and sustainability in material handling operations worldwide.

The surge in demand for Battery Analytics for MHE is largely attributed to the growing emphasis on optimizing fleet performance and minimizing operational downtime. As industries such as warehousing, logistics, and manufacturing continue to expand, there is a heightened need for real-time battery monitoring and predictive maintenance. Battery analytics platforms empower organizations to proactively manage battery health, extend battery lifespan, and reduce unscheduled maintenance. This not only ensures uninterrupted operations but also significantly lowers total cost of ownership, making battery analytics an indispensable tool in modern material handling environments.

Another significant growth factor is the rapid technological advancements in battery chemistry and analytics software. The integration of IoT sensors, artificial intelligence, and machine learning algorithms into battery analytics solutions has revolutionized the way data is collected, analyzed, and utilized. These technologies enable precise monitoring of battery parameters such as charge cycles, temperature, and voltage, delivering actionable insights that enhance decision-making. As a result, companies are increasingly investing in advanced battery analytics to gain a competitive edge, improve energy efficiency, and comply with stringent environmental regulations.

Sustainability and environmental concerns are also propelling the adoption of Battery Analytics for MHE. With global industries under pressure to reduce their carbon footprint, optimizing battery usage and ensuring responsible battery disposal have become priorities. Battery analytics solutions facilitate the transition to greener practices by maximizing the utilization of existing batteries and supporting the adoption of eco-friendly battery types such as lithium-ion. This aligns with broader corporate sustainability goals and regulatory requirements, further accelerating market growth.

From a regional perspective, Asia Pacific currently leads the Battery Analytics for MHE market, accounting for the largest share due to the region's booming manufacturing and e-commerce sectors. North America and Europe follow closely, driven by technological innovation and strong regulatory support for clean energy initiatives. While Latin America and the Middle East & Africa are still emerging markets, they are expected to witness accelerated growth during the forecast period as industrialization and automation gain momentum.

Component Analysis

The Battery Analytics for MHE market is segmented by component into software, hardware, and services, each playing a crucial role in the ecosystem. The software segment represents the largest revenue share, as businesses increasingly rely on advanced analytics platforms for real-time battery monitoring, predictive maintenance, and performance optimization. These software solutions leverage big data analytics, AI, and machine learning to provide actionable insights that drive operational efficiency. The demand for user-friendly interfaces and customizable dashboards is also fueling innovation in this segment, enabling end-users to tailor analytics to their specific operational needs.

The hardware segment encompasses IoT sensors, data loggers, and other monitoring devices that collect critical information from batteries in material handling equipment. The proliferat

The Germany Rechargeable Battery Market report segments the industry into Technology (Lithium-Ion, Lead-Acid, Other Technologies (NiMH, NiCd, etc.)), Application (Automotive Batteries, Industrial Batteries (Motive, Stationary (Telecom, UPS, Energy Storage Systems (ESS), etc.), Portable Batteries (Consumer Electronics, etc.), Other Applications). Get five years of historical data alongside five-year market forecasts.

The lithium-ion battery digital solution market is experiencing robust growth, driven by the increasing demand for electric vehicles (EVs) and energy storage systems (ESS). The market, estimated at $50 billion in 2025, is projected to exhibit a Compound Annual Growth Rate (CAGR) of 15% from 2025 to 2033, reaching an impressive $150 billion by 2033. This expansion is fueled by several key factors. Firstly, the ongoing digital transformation within the battery manufacturing sector is leading to the adoption of advanced digital twins, predictive maintenance solutions, and data analytics for optimizing production processes and enhancing battery performance. Secondly, the rising need for improved battery safety and lifecycle management is driving the demand for sophisticated digital solutions that can monitor battery health, predict potential failures, and optimize charging strategies. Finally, government regulations promoting EV adoption and investments in grid-scale energy storage are further accelerating market growth. Key players like CATL, LG Chem, Panasonic, BYD, and Samsung are at the forefront of this technological revolution, investing heavily in research and development to deliver cutting-edge digital solutions. However, the market faces certain challenges. The high initial investment costs associated with implementing digital solutions can be a barrier to entry for smaller players. Furthermore, data security and privacy concerns, along with the need for skilled professionals to manage and interpret complex data sets, pose significant hurdles. Despite these constraints, the long-term outlook for the lithium-ion battery digital solution market remains incredibly positive. The increasing focus on sustainability, coupled with advancements in battery technology and the ever-growing demand for clean energy, will continue to propel market expansion in the coming years. Regional variations will likely be significant, with North America and Asia expected to dominate the market share due to strong EV adoption and substantial investments in battery manufacturing.

Snapshot img

Lithium-Ion Battery Market Size 2025-2029

The lithium-ion battery market size is forecast to increase by USD 405.1 billion, at a CAGR of 34.5% between 2024 and 2029.

The market is experiencing robust growth, driven primarily by the surging demand from the consumer electronics sector. The insatiable appetite for portable devices, electric vehicles, and renewable energy storage systems is fueling the market's expansion. Additionally, legislative initiatives supporting battery recycling are creating new opportunities for market participants. However, the market is not without challenges. The increasing popularity of fuel cell solutions, which offer greater energy density and longer runtimes, poses a significant threat to lithium-ion batteries. Moreover, the environmental concerns surrounding the extraction and disposal of lithium, a key component in these batteries, could hamper market growth.
Companies must navigate these challenges by investing in research and development to improve battery efficiency and sustainability, as well as exploring alternative sources for lithium and recycling initiatives. The market's dynamics underscore the need for strategic planning and innovation to capitalize on emerging opportunities and maintain a competitive edge.

What will be the Size of the Lithium-Ion Battery Market during the forecast period?

Explore in-depth regional segment analysis with market size data - historical 2019-2023 and forecasts 2025-2029 - in the full report.
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The market continues to evolve, driven by advancements in technology and increasing demand across various sectors. Rechargeable batteries, a key component of this market, are subject to ongoing research and development to enhance their performance and safety. Discharge rate, battery pack size, resistance, and capacity are critical factors influencing battery performance. Range anxiety, a concern for electric vehicle (EV) consumers, is being addressed through advancements in battery technology and charging infrastructure. Battery pack safety is a paramount concern, with ongoing efforts to improve battery management systems (BMS) and battery pack management. BMS optimizes battery usage, ensuring efficient charging and discharging, while battery pack management focuses on durability and reliability.

Lithium-ion batteries, with their high energy density, are popular in sectors ranging from consumer electronics to transportation. Battery cost, a significant market driver, is influenced by factors such as battery pack design, cell chemistry, and manufacturing processes. Battery testing and recycling are essential for ensuring battery durability and sustainability. Thermal management, battery impedance, and charging infrastructure are other critical factors shaping the market. Fast charging, a desirable feature for consumers, is driving innovation in battery technology. Lithium-ion polymer batteries and lithium cobalt oxide, lithium manganese oxide, and lithium iron phosphate are among the various cell chemistries being explored to improve battery efficiency and reliability.The continuous unfolding of market activities underscores the dynamic nature of the market.

How is this Lithium-Ion Battery Industry segmented?

The lithium-ion battery industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD billion' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.

Type

  Lithium nickel manganese cobalt
  Lithium titanate
  Lithium iron phosphate
  Lithium cobalt oxide


Application

  Automotive
  Consumer electronics
  Others


Voltage

  Low (Below 12V)
  Medium (12V - 36V)
  High (Above 36V)


Capacity

  Below 3,000 mAh
  3,001-10,000 mAh
  10,001-60,000 mAh
  Above 60,000 mAh


Geography

  North America

    US


  Europe

    France
    Germany
    Italy
    Sweden
    UK


  APAC

    China
    India
    Japan
    South Korea


  Rest of World (ROW)

By Type Insights

The lithium nickel manganese cobalt segment is estimated to witness significant growth during the forecast period.

Lithium-ion batteries, specifically lithium nickel manganese cobalt (NMC) batteries, have gained significant traction in various industries due to their unique properties. The combination of nickel and manganese in these batteries offers advantages from both worlds. Manganese, with its low internal resistance, forms a spinel structure, which is beneficial for creating batteries with low resistance. Nickel, despite having a larger specific energy, is unstable. By blending these metals, the strengths of each are amplified, resulting in high-performing batteries. NMC batteries are widely adopted in power tools, e-bikes, and other electric drivetrains due to their versatility. They cater to both high-energy and high-power applications, m

The UPS Battery for Data Center market is experiencing robust growth, projected to be a $5.64 billion market in 2025, expanding at a Compound Annual Growth Rate (CAGR) of 6.59% from 2025 to 2033. This expansion is driven by the increasing reliance on data centers globally, fueled by the exponential growth of cloud computing, big data analytics, and the Internet of Things (IoT). The rising demand for higher uptime and reliability in data centers necessitates advanced UPS battery systems capable of handling larger power demands and providing seamless power backup during outages. This preference for improved power protection is further intensified by stringent regulatory compliance requirements and the increasing frequency of power disruptions in many regions. Lithium-ion batteries are steadily gaining market share over lead-acid batteries due to their superior energy density, longer lifespan, and lower maintenance requirements, though the higher initial cost remains a factor influencing adoption rates. The market is segmented by application (Tier 1-4 data centers) and battery type (lead-acid and lithium-ion), with Tier 3 and Tier 4 data centers representing significant growth segments. Geographic growth is expected across North America (particularly the US), Europe (Germany, UK, France), APAC (India), and other regions, reflecting the global distribution of data center infrastructure and digital transformation initiatives. Competition is intense, with established players like Eaton, Schneider Electric, and EnerSys competing against emerging technology providers. The market's future hinges on technological advancements in battery technology, particularly focusing on enhancing energy density, improving safety, and reducing costs, as well as overcoming challenges related to battery recycling and environmental concerns. The competitive landscape is characterized by a mix of established players and emerging companies vying for market dominance. Key strategies include product innovation, strategic partnerships, and mergers and acquisitions to expand product portfolios and geographic reach. Companies are focusing on providing comprehensive solutions that include not only batteries but also related services such as installation, maintenance, and lifecycle management. The industry faces risks associated with fluctuating raw material prices, supply chain disruptions, and the evolving regulatory landscape regarding battery safety and disposal. Furthermore, the continuous advancement of battery technology requires companies to adapt quickly and invest in research and development to maintain their competitive edge. Despite these challenges, the long-term outlook for the UPS battery market for data centers remains positive, driven by the unrelenting growth of the digital economy and the critical need for reliable power backup in the data center infrastructure.

Battery Analytics for MHE Market Outlook

According to our latest research, the global Battery Analytics for MHE market size reached USD 1.02 billion in 2024, driven by the accelerating adoption of data-driven solutions in material handling environments. The market is poised for robust growth, expanding at a CAGR of 14.6% from 2025 to 2033. By the end of 2033, the market is forecasted to achieve a size of USD 3.06 billion. This growth is underpinned by increasing investments in automation, the rapid expansion of e-commerce, and the critical need for operational efficiency in logistics and warehousing sectors.

One of the primary growth factors for the Battery Analytics for MHE market is the rising demand for real-time monitoring and predictive maintenance across material handling equipment fleets. Organizations are increasingly turning to advanced analytics tools to optimize battery usage, extend equipment life, and reduce downtime. The integration of IoT sensors and cloud-based analytics platforms enables continuous tracking of battery health, charging cycles, and energy consumption. This data-driven approach not only enhances asset reliability but also helps in identifying potential failures before they occur, thereby minimizing operational disruptions and maintenance costs. As a result, battery analytics solutions are becoming indispensable for companies aiming to maximize productivity and efficiency in their material handling operations.

A second critical growth driver is the surging adoption of electric-powered material handling equipment, particularly in sectors such as e-commerce, automotive, and food & beverage. The global shift towards sustainability and the implementation of stringent emission regulations have prompted organizations to replace traditional internal combustion engine-powered equipment with battery-operated alternatives. This transition has created a pressing need for sophisticated battery management and analytics systems to ensure optimal performance and longevity of these assets. Furthermore, the growing complexity of multi-site and multi-shift operations necessitates advanced analytics capabilities to manage battery fleets efficiently. This trend is further amplified by the proliferation of automation and robotics in warehousing and logistics, where uninterrupted power supply and efficient battery management are mission-critical.

Additionally, the proliferation of cloud computing and advancements in machine learning algorithms are significantly enhancing the capabilities of battery analytics platforms. Cloud-based deployment models allow for scalable, centralized management of battery data across geographically dispersed facilities, enabling organizations to derive actionable insights and benchmark performance on a global scale. Machine learning-driven analytics can predict battery degradation patterns, optimize charging schedules, and recommend proactive maintenance actions, thereby reducing total cost of ownership. The convergence of these technologies is not only transforming battery analytics for MHE but also paving the way for new business models such as battery-as-a-service and performance-based maintenance contracts, which further stimulate market growth.

Regionally, Asia Pacific is emerging as the fastest-growing market for battery analytics in material handling equipment, driven by rapid industrialization, the expansion of e-commerce giants, and significant investments in smart warehousing infrastructure. North America and Europe continue to maintain strong market positions due to the early adoption of automation technologies, well-established logistics networks, and a strong focus on operational efficiency. Meanwhile, Latin America and the Middle East & Africa are witnessing increasing adoption rates as local industries modernize and global supply chains extend into these regions. The competitive landscape is evolving, with global and regional players investing in R&D and strategic partnerships to address the specific needs of diverse end-user segments across these regions.

Component Analysis

The component segment of the Battery Analytics for MHE market is categorized into software, hardware, and services, each playing a crucial role in the overall ecosystem. Software solutions are the backbone of battery analytics, providing advanced algorithms for data processing, visualization, and predictive analytics. These platforms integrate seamlessly with both on-prem

The global all-solid-state lithium-ion battery market is projected to grow from a value of approximately 180 million in 2025 to reach around 3,115 million by 2033, exhibiting a CAGR of 35.6% during the forecast period. This substantial growth can be attributed to the rising demand for electric vehicles, the increasing adoption of renewable energy sources, and the growing need for lightweight and high-energy-density batteries in portable electronic devices. Furthermore, the market is driven by the advantages offered by all-solid-state lithium-ion batteries, such as their higher energy density, longer cycle life, improved safety, and wider operating temperature range compared to conventional lithium-ion batteries. Key market players such as BMW, Hyundai, Dyson, Apple, CATL, and others are actively involved in research and development to enhance the performance and reduce the cost of all-solid-state lithium-ion batteries, which is expected to further accelerate market growth. A detailed analysis of the market, including market size, CAGR, drivers, trends, restraints, segments (application and type), company profiles, and region-specific data, is provided in the report.

Battery Analytics Platform Market Outlook

According to our latest research, the global battery analytics platform market size reached USD 1.42 billion in 2024, demonstrating robust momentum driven by the surging adoption of electric vehicles and renewable energy storage solutions. The market is poised to expand at a CAGR of 16.8% from 2025 to 2033, translating to a forecasted market value of USD 6.00 billion by 2033. This impressive growth trajectory is primarily fueled by the increasing need for real-time battery health monitoring, predictive maintenance, and efficient energy management across diverse industries.

The primary growth driver for the battery analytics platform market is the accelerating electrification of transportation and the rapid proliferation of electric vehicles (EVs) worldwide. As automotive manufacturers and fleet operators integrate larger and more advanced battery systems, the demand for sophisticated analytics platforms capable of monitoring battery performance, predicting failures, and optimizing charging cycles has intensified. Battery analytics platforms leverage artificial intelligence, machine learning, and big data analytics to deliver actionable insights, ensuring greater safety, longer battery life, and reduced operational costs. This technological evolution is not only transforming the automotive sector but also creating ripple effects across energy storage and consumer electronics, further propelling market expansion.

Another significant growth factor is the rising deployment of grid-scale energy storage systems, particularly as utilities and independent power producers integrate renewable energy sources such as solar and wind. The intermittent nature of renewables necessitates advanced battery analytics platforms to manage storage assets efficiently, maintain grid stability, and optimize energy dispatch. These platforms provide utilities with real-time visibility into battery state-of-health, degradation patterns, and usage forecasts, enabling proactive maintenance and minimizing downtime. Additionally, regulatory mandates focusing on sustainability and grid reliability are compelling utilities to adopt analytics-driven solutions, thereby catalyzing market growth.

The evolution of battery technologies, coupled with the growing complexity of multi-chemistry and multi-format battery systems, has further underscored the need for robust analytics platforms. In sectors such as industrial equipment and consumer electronics, where downtime can result in significant financial losses, predictive analytics and failure diagnostics are becoming indispensable. Battery analytics platforms are increasingly being integrated into manufacturing and supply chain operations to monitor battery quality, traceability, and lifecycle management. This trend is expected to intensify as manufacturers seek to enhance product reliability and comply with stringent regulatory standards related to safety and environmental impact.

From a regional perspective, Asia Pacific continues to dominate the battery analytics platform market, accounting for the largest share in 2024, primarily due to the region’s leadership in battery manufacturing, electric vehicle adoption, and renewable energy investments. North America and Europe are also witnessing substantial growth, driven by robust R&D activities, supportive government policies, and the presence of major automotive and technology companies. Latin America and the Middle East & Africa are emerging as high-potential markets, fueled by infrastructural development and increasing investments in clean energy. The interplay of these regional dynamics is shaping the competitive landscape and driving innovation across the global battery analytics platform market.

Component Analysis

The battery analytics platform market is segmented by component into software and services, both of which play critical roles in delivering comprehensive battery management solutions. The software segment encompasses advanced analytics

The Data Center Energy Storage Battery market is experiencing robust growth, driven by the increasing demand for reliable and efficient power backup solutions within the rapidly expanding data center industry. The rising adoption of cloud computing, edge computing, and the proliferation of data-intensive applications are key factors fueling this market expansion. Furthermore, the growing concerns regarding power outages and their potential impact on data center operations are prompting businesses to invest heavily in energy storage solutions. Lithium-ion batteries currently dominate the market due to their higher energy density and longer lifespan compared to lead-acid batteries, although lead-acid batteries still hold a significant share, particularly in applications requiring lower cost solutions. The market is segmented by application (Internet industry, finance and insurance, manufacturing, government, and others) and battery type (lead-acid, lithium-ion, and others), with the Internet industry currently representing the largest segment. Geographic expansion is also significant, with North America and Asia Pacific anticipated to lead in market share due to the high concentration of data centers and strong government initiatives promoting renewable energy integration. However, factors such as the high initial investment cost of energy storage systems and the need for robust safety protocols and maintenance present challenges to market growth. We project a continued strong CAGR for the foreseeable future, with lithium-ion technology increasingly gaining traction as costs decrease and performance improves. The competitive landscape is marked by a mix of established players and emerging companies. Key players like LG Chem, EnerSys, GS Yuasa, and Samsung SDI are leveraging their technological expertise and extensive distribution networks to maintain a strong foothold. However, the market also exhibits a growing presence of Chinese manufacturers, who are increasingly competitive in terms of pricing and production capacity. The market is characterized by intense competition, with players focusing on innovation, cost reduction, and strategic partnerships to enhance their market position. Future growth will depend on advancements in battery technology, decreasing costs, improved safety regulations, and supportive government policies aimed at promoting renewable energy integration and grid stability within data center infrastructure.

Battery Monitoring Software Market size was valued at USD 1.07 Billion in 2023 and is projected to reach USD 3.10 Billion by 2030, growing at a CAGR of 16.8% during the forecast period 2024-2030.

Global Battery Monitoring Software Market Drivers

The market drivers for the Battery Monitoring Software Market can be influenced by various factors. These may include:

Growing Need for Energy Storage: The demand for effective energy storage solutions has increased due to the growing use of electric vehicles and renewable energy sources. The best possible control of these energy storage systems is made possible by battery monitoring software.

Growth in Data Center and Industrial Applications: Backup power systems play a major role in data centers and industries. Software for battery monitoring aids in guaranteeing these vital power backup systems' dependability and efficiency.

Emphasis on Preventive Maintenance: To avoid expensive downtime and battery failures, businesses are placing a greater emphasis on proactive maintenance techniques. Software for monitoring batteries offers in-the-moment knowledge to anticipate and avert possible problems.

Strict criteria and Regulations: The use of monitoring software is prompted by the need to comply with strict criteria for battery performance, safety, and the environment.

Growing Usage of Lithium-Ion Batteries: Because lithium-ion batteries are sensitive to temperature and charge, they must be closely monitored in a variety of applications. Software for monitoring aids in maximizing both their efficiency and security.

Remote Monitoring Capabilities: As the Internet of Things and connection expand, so are the opportunities for remote battery management and monitoring across different places. This has led to an increase in the use of monitoring software.

Concentrate on Optimal Battery Performance: In order to minimize replacement expenses, businesses aim to extend the life and efficiency of batteries. Optimizing charging, discharging, and overall battery health is made easier with the help of monitoring software.

The global Lead Battery Management System market is anticipated to reach a value of over USD XXX million by 2033, exhibiting a CAGR of approximately XX% during the forecast period. The growing demand for uninterrupted power supply in critical applications, such as data centers, telecommunications, and healthcare facilities, is primarily driving the market growth. Additionally, the increasing adoption of electric vehicles and hybrid vehicles, which rely on lead-acid batteries for power storage, is further augmenting market demand. The market is segmented based on application into data centers, transportation, communication, finance, and other industries. Data centers account for a significant share of the market due to their need for reliable power backup systems. The transportation segment is also expected to witness substantial growth, driven by the increasing demand for electric vehicles. Geographically, North America and Europe currently dominate the market, but Asia-Pacific is expected to emerge as a key growth region due to the increasing adoption of lead-acid batteries in automotive and industrial applications.

The Battery State of Health (SOH) Monitor market is experiencing robust growth, driven by the increasing demand for electric vehicles (EVs), energy storage systems (ESS), and portable electronic devices. The market's expansion is fueled by the critical need for accurate battery health monitoring to optimize battery lifespan, improve safety, and prevent unexpected failures. Advancements in sensor technology, data analytics, and sophisticated algorithms are enabling more precise and reliable SOH estimations, leading to increased adoption across various applications. The lithium-ion battery segment dominates the market due to its prevalence in EVs and ESS, while the demand for SOH monitors in portable electronics is also substantial, contributing significantly to market growth. Different battery types (lead-acid, Ni-Cd, NiMH) also present distinct monitoring challenges and opportunities, driving the development of specialized SOH monitoring solutions. Geographically, North America and Europe are currently leading the market, driven by strong government regulations supporting EV adoption and a well-established infrastructure for battery management. However, the Asia-Pacific region is projected to experience the fastest growth, fueled by burgeoning EV manufacturing and a rapidly expanding consumer electronics market. The market faces certain restraints, including the high initial investment costs associated with implementing SOH monitoring systems and the complexities involved in integrating these systems into diverse battery chemistries and applications. However, ongoing technological advancements and decreasing costs are expected to alleviate these constraints over time, leading to wider market penetration. The forecast period of 2025-2033 promises continued expansion, primarily driven by the increasing adoption of EVs globally and the ongoing development of smart grids, requiring advanced battery management solutions. The market segmentation by battery type and application presents significant opportunities for specialized SOH monitor manufacturers. The incorporation of advanced machine learning techniques into SOH algorithms enhances accuracy and predictive capabilities, further driving market demand. Competitive landscape analysis reveals a mix of established players and emerging technology providers, with a focus on innovative solutions and strategic partnerships to enhance market share. The ongoing development of high-capacity, long-life batteries necessitates precise SOH monitoring, strengthening the market's long-term growth trajectory. Regions with robust policies supporting renewable energy integration and EV adoption are likely to experience faster growth rates than others.

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Aqueous Batteries Market Size 2025-2029

The aqueous batteries market size is forecast to increase by USD 735.7 million at a CAGR of 25.4% between 2024 and 2029.

The market is experiencing significant growth, driven by the increasing demand for eco-friendly and cost-effective energy solutions. The transition towards sustainable energy sources and the rising adoption of electric vehicles (EVs) are key factors fueling market expansion. However, regulatory hurdles impact adoption, as stringent regulations and approval processes can delay market entry for new players. Additionally, supply chain inconsistencies temper growth potential due to the complex nature of manufacturing aqueous batteries and the need for specialized components. One of the key trends shaping this market is the growing preference for Absorbed Glass Mat (AGM) batteries and lithium-ion batteries.
Despite these challenges, companies can capitalize on the market's potential by focusing on innovation, regulatory compliance, and establishing robust supply chains. Additionally, the growing adoption of electric and hybrid vehicles is expected to disrupt the traditional market, as these vehicles rely on different types of batteries for power. By addressing these obstacles, businesses can effectively navigate the competitive landscape and capitalize on the growing demand for sustainable energy solutions.

What will be the Size of the Aqueous Batteries Market during the forecast period?

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The market is experiencing significant growth, driven by the integration of the Internet of Things (IoT) into energy infrastructure and the adoption of smart grid technologies. Load leveling and energy trading are key applications, enabling carbon emissions reduction and grid reliability. Data visualization and big data analysis, facilitated by cloud computing, enhance energy policy and climate change mitigation efforts. Grid modernization, including energy dashboards and power management systems, optimize energy markets and energy storage systems.
Hybrid flow batteries, such as zinc-bromine, play a crucial role in energy resilience and renewable energy deployment. Energy arbitrage and power electronics further boost grid efficiency and flexibility. Digital twins and distributed energy resources enable real-time monitoring and optimization, ensuring a sustainable energy future.

How is this Aqueous Batteries Industry segmented?

The aqueous batteries industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.

Type

  Aqueous Li-ion battery
  Aqueous Zinc-ion battery
  Others


Application

  Electric vehicle
  Energy storage
  Consumer electronics
  Others


End-user

  Utility sector
  Automotive
  Electronics manufacturers
  Government and military


Geography

  North America

    US
    Canada


  Europe

    France
    Germany
    Italy
    UK


  APAC

    China
    Japan
    South Korea


  South America

    Brazil


  Rest of World (ROW)

By Type Insights

The aqueous li-ion battery segment is estimated to witness significant growth during the forecast period. Aqueous Li-ion batteries have emerged as a significant and promising segment in the market, offering advantages such as enhanced safety, lower cost, and environmental sustainability compared to traditional non-aqueous Li-ion batteries. The increasing demand for safe and efficient energy storage solutions across various industries, including renewable energy integration, frequency regulation, and power quality, has positioned aqueous Li-ion batteries as a key player in the evolving battery technology landscape. In September 2024, the U.S. Department of Energy announced a USD 62.5 million funding commitment for the Aqueous Battery Consortium, a major research initiative led by Stanford University and SLAC National Accelerator Laboratory.

This investment underscores the potential of aqueous Li-ion batteries to address the energy storage needs of utility-scale applications, distributed generation, and grid storage. The integration of aqueous Li-ion batteries in renewable energy sources, such as wind and solar energy, contributes to energy efficiency and energy security. These batteries also offer long cycle life, energy density, and depth of discharge, making them suitable for applications like electric vehicles, peak shaving, and self-discharge rate reduction. Aqueous Li-ion batteries are also environmentally friendly, with a lower carbon footprint and reduced environmental impact compared to traditional batteries like nickel-cadmium and lead-acid batteries.

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The Aqueous Li-ion battery segment was valued at USD 136.80 million in 2019 and showed a gradual increase during the forecast period. F