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.

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

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.

Battery Cell Formation Data Analytics Market Outlook

According to our latest research, the global battery cell formation data analytics market size reached USD 1.45 billion in 2024, reflecting the rapid adoption of advanced data analytics solutions within the battery manufacturing sector. The market is set to expand at a robust CAGR of 18.9% from 2025 to 2033, driven by the increasing demand for high-performance batteries and the need for greater operational efficiency. By the end of 2033, the market is forecasted to reach approximately USD 7.39 billion, underscoring the transformative impact of analytics on battery cell formation processes. This remarkable growth is propelled by the integration of artificial intelligence, machine learning, and IoT technologies, which are revolutionizing the way battery manufacturers optimize formation cycles, enhance quality control, and reduce production costs.

One of the primary growth factors for the battery cell formation data analytics market is the surging demand for electric vehicles (EVs) worldwide. As governments enforce stricter emission regulations and automotive OEMs commit to electrification, the pressure to deliver robust, long-lasting batteries has intensified. Battery cell formation, a critical stage in the production process, directly influences the final performance and safety of battery packs. Advanced data analytics solutions enable manufacturers to monitor and analyze key parameters during formation, such as voltage, current, and temperature, in real time. By leveraging these insights, manufacturers can identify anomalies, optimize charge-discharge cycles, and significantly reduce defect rates. This not only ensures the production of high-quality batteries but also shortens time-to-market, giving companies a competitive edge in the fast-evolving EV landscape.

Another significant driver is the proliferation of consumer electronics and energy storage systems (ESS), both of which rely on high-density, reliable batteries. The rapid expansion of IoT devices, smartphones, laptops, and renewable energy installations has placed unprecedented demands on battery performance and safety. Battery cell formation data analytics platforms empower manufacturers to achieve precise control over cell formation protocols, resulting in batteries with consistent capacity, longer cycle life, and enhanced safety profiles. Furthermore, predictive analytics tools help in forecasting potential failures and optimizing maintenance schedules, thereby reducing operational downtime and warranty costs. As the complexity and scale of battery production increase, the adoption of sophisticated analytics platforms is becoming indispensable for maintaining product quality and operational efficiency.

The integration of Industry 4.0 technologies, such as automation, cloud computing, and digital twins, is further accelerating the adoption of data analytics in battery cell formation. Manufacturers are increasingly investing in smart factories, where interconnected devices and sensors generate vast amounts of data throughout the production line. By harnessing this data through advanced analytics, companies can implement closed-loop control systems, automate quality assurance, and enable real-time decision-making. This digital transformation is not only enhancing production yields but also facilitating compliance with stringent industry standards and regulatory requirements. As a result, the battery cell formation data analytics market is witnessing robust investments from both established players and emerging startups aiming to capitalize on the digitalization trend.

Regionally, Asia Pacific dominates the global market, accounting for the largest share in 2024, driven by the presence of leading battery manufacturers in China, South Korea, and Japan. North America and Europe are also experiencing significant growth, fueled by strong investments in EV infrastructure, energy storage projects, and the localization of battery supply chains. The Middle East & Africa and Latin America, while still emerging, are gradually adopting advanced analytics solutions as battery demand rises in these regions. Overall, the regional outlook for the battery cell formation data analytics market remains highly favorable, supported by government incentives, technological advancements, and the global shift towards sustainable energy solutions.

Component Analysis

The component segment of the battery cell formation data analytics market is categorized into softwa

A set of Li-ion batteries were run through different operational profiles (charge, discharge and impedance) at various temperatures. Impedance measurement was carried out through an electrochemical impedance spectroscopy (EIS) frequency.

Repeated charge and discharge cycles result in accelerated aging of the batteries while impedance measurements provide insight into the internal battery parameters that change as aging progresses. The experiments were stopped when the batteries reached end-of-life (EOL) criteria. These datasets can be used for the prediction of both remaining charge (for a given discharge cycle) and remaining useful life (RUL). Data are in Batch of 6 experiments, data provided in .mat files with experiment details in associated READEME.txt -

EV Battery Analytics Software Market Outlook

According to our latest research, the EV Battery Analytics Software market size reached USD 1.47 billion in 2024, demonstrating robust growth across the electric vehicle ecosystem. The market is projected to expand at a CAGR of 18.5% from 2025 to 2033, reaching an estimated USD 6.24 billion by 2033. This surge is primarily driven by the rapid adoption of electric vehicles globally, advancements in battery technology, and the growing need for real-time battery data analytics to optimize performance, safety, and lifecycle management.

One of the principal growth factors fueling the EV Battery Analytics Software market is the exponential increase in electric vehicle (EV) adoption, both in passenger and commercial segments. As governments worldwide enforce stricter emission regulations and incentivize EV purchases, the deployment of EVs has soared, necessitating sophisticated analytics platforms to monitor battery health, predict failures, and maximize battery lifespan. These analytics solutions enable OEMs and fleet operators to leverage data-driven insights, reducing operational costs and enhancing vehicle reliability. Furthermore, the proliferation of connected vehicles and IoT technologies has made it feasible to collect and process vast datasets from batteries in real time, further underpinning the demand for advanced analytics solutions.

In addition to regulatory and technological drivers, the increasing complexity and diversity of battery chemistries have amplified the need for specialized analytics software. Modern batteries, such as lithium-ion, solid-state, and emerging chemistries, require tailored monitoring and predictive maintenance to ensure safety and efficiency. The ability of EV battery analytics software to provide early warnings for potential failures, optimize charging cycles, and facilitate warranty management is becoming indispensable for automotive OEMs, battery manufacturers, and fleet operators. This trend is particularly pronounced in regions where EV penetration is accelerating, such as Asia Pacific and Europe, thereby boosting the uptake of analytics platforms tailored to regional requirements and regulatory standards.

Another significant driver is the evolution of business models in the EV ecosystem, including battery leasing, swapping, and second-life applications. These models demand granular visibility into battery usage patterns, degradation rates, and residual value estimation, all of which are addressed by advanced analytics software. The integration of artificial intelligence and machine learning in analytics platforms is enabling predictive maintenance, real-time diagnostics, and enhanced energy management, creating new revenue streams for software vendors and service providers. As the industry moves toward a circular economy and sustainability, the role of analytics in enabling efficient battery lifecycle management is becoming increasingly critical.

Regionally, Asia Pacific dominates the EV Battery Analytics Software market, accounting for over 40% of the global revenue in 2024, driven by the sheer volume of EV production and battery manufacturing in China, Japan, and South Korea. North America and Europe are also witnessing significant growth, fueled by supportive government policies, expanding charging infrastructure, and the presence of leading automotive OEMs. While Latin America and the Middle East & Africa are currently smaller markets, they are expected to register above-average growth rates as EV adoption accelerates and supportive regulatory frameworks are implemented. Overall, the global landscape is characterized by intense competition, rapid technological innovation, and a growing emphasis on sustainability and efficiency in battery management.

Component Analysis

The EV Battery Analytics Software market is segmented by component into software and services, each playing a pivotal role in the ecosystem. The software segment comprises platforms and solutions designed to analyze battery data, provide real-time monitoring, and generate actionable insights for end users. These software solutions leverage advanced algorithms, machine learning, and artificial intelligence to process vast amounts of data generated by EV batteries, enabling predictive maintenance, warranty analytics, and energy management. As EV adoption grows, automotive OEMs and fleet operators are increasingly investing in proprietary and third-party analytics platforms to gain competitive advantage

The Data Center Lithium-ion Battery market is booming, projected to reach $506 million in 2025 and grow at a CAGR of 9.8% through 2033. Driven by cloud computing and IoT expansion, this report analyzes market trends, key players (Huawei, Eaton, Schneider Electric), and regional growth, offering insights for investors and industry professionals.

Second-Life EV Battery Analytics Market Outlook

According to our latest research, the global second-life EV battery analytics market size reached USD 465 million in 2024, propelled by the increasing adoption of electric vehicles and the urgent need for sustainable energy storage solutions. The market is experiencing robust momentum, registering a CAGR of 22.1% from 2025 to 2033. By the end of 2033, the market is projected to achieve a value of USD 2.42 billion, reflecting a substantial expansion driven by technological advancements, regulatory incentives, and the rising focus on circular economy principles. The growing emphasis on maximizing the lifecycle value of EV batteries and integrating them into stationary storage applications are key contributors to this growth trajectory.

One of the primary growth factors for the second-life EV battery analytics market is the global shift towards decarbonization and renewable energy integration. As governments and organizations intensify their efforts to reduce carbon emissions, there is a significant push to repurpose EV batteries after their automotive life for stationary energy storage, grid stabilization, and renewable integration. Analytics platforms play a crucial role in determining the health, performance, and remaining useful life of these batteries, enabling stakeholders to make informed decisions regarding their redeployment. The ability to predict battery degradation, optimize usage, and minimize operational risks through advanced analytics is driving widespread adoption among utilities, commercial and industrial entities, and even residential users.

Another critical driver is the rapidly expanding electric vehicle market, which is resulting in a growing pool of used batteries suitable for second-life applications. With millions of EVs expected to reach the end of their first lifecycle in the coming years, there is an increasing availability of batteries that can be repurposed, provided their health and performance are accurately assessed. Second-life battery analytics platforms leverage artificial intelligence, machine learning, and big data techniques to analyze battery data, predict future performance, and ensure safety and reliability in secondary applications. This technological sophistication not only extends the economic value of batteries but also supports sustainability by reducing waste and conserving raw materials.

Furthermore, regulatory frameworks and policy incentives are catalyzing the growth of the second-life EV battery analytics market. Governments in regions such as Europe, North America, and Asia Pacific are implementing policies that encourage battery recycling, reuse, and responsible disposal. These regulations often require rigorous monitoring and reporting of battery health, safety, and environmental impact, which can only be achieved through robust analytics solutions. The alignment of industry standards and the development of interoperable analytics platforms are further enhancing market opportunities, as stakeholders seek to comply with evolving regulations while maximizing the value of second-life batteries.

From a regional perspective, Asia Pacific is emerging as a dominant force in the second-life EV battery analytics market, supported by the rapid adoption of electric vehicles in China, Japan, and South Korea. North America and Europe are also significant contributors, driven by strong regulatory support, advanced technology ecosystems, and a mature EV infrastructure. Latin America and the Middle East & Africa are gradually catching up, leveraging international collaborations and pilot projects to explore the potential of second-life battery analytics in local energy systems. Each region presents unique market dynamics, influenced by local policy frameworks, EV adoption rates, and the maturity of energy storage markets.

Battery Type Analysis

The battery type segment is a crucial determinant of the second-life EV battery analytics market, as it directly influences the tech

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. Augmented demand from consumer electronics will drive the lithium-ion battery market.

Major Market Trends & Insights

APAC dominated the market and accounted for a 52% growth during the forecast period.
By Type - Lithium nickel manganese cobalt segment was valued at USD 13.80 billion in 2023
By Application - Automotive segment accounted for the largest market revenue share in 2023

Market Size & Forecast

Market Opportunities: USD 1.00 billion
Market Future Opportunities: USD 405.10 billion 
CAGR : 34.5%
APAC: Largest market in 2023

Market Summary

The market is a dynamic and ever-evolving landscape shaped by advancements in core technologies and their applications. This market's growth is primarily driven by the augmented demand for lithium-ion batteries in consumer electronics, such as smartphones and laptops. Furthermore, legislative support for battery recycling and the growing popularity of fuel cell solutions are creating new opportunities for market expansion. According to recent studies, the market is projected to account for over 50% of the global rechargeable battery market by 2025.
In related markets such as electric vehicles, lithium-ion batteries hold an even larger market share. Despite these opportunities, challenges persist, including the high cost of raw materials and safety concerns. As the market continues to unfold, stakeholders must navigate these challenges and capitalize on emerging trends to remain competitive.

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

Get Key Insights on Market Forecast (PDF) Request Free Sample

How is the Lithium-Ion Battery Market Segmented and what are the key trends of market segmentation?

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 those with nickel, manganese, and cobalt (NMC) cathodes, have gained significant traction in various industries due to their unique properties. NMC batteries offer a balance between energy density and power density, making them suitable for diverse applications. Graphite anodes, a traditional choice, contribute to high energy density, while NMC cathodes provide power density. Fast charging is a crucial aspect, with NMC batteries demonstrating impressive progress in this area. Power density has increased by 15%, enabling quicker charge times. Battery pack design plays a pivotal role in market trends. Silicon anodes and lithium iron phosphate (LFP) cathodes are emerging alternatives, offering advantages such as improved energy density and longer cycle life.

Solid-state batteries are another promising development, with potential for enhanced safety and energy density. Battery management systems and power electronics are essential components, ensuring optimal battery performance. Recycling processes are increasingly important, with a 12% increase in recycling rates to mitigate environmental concerns. Material science, electrolyte composition, and electrode kinetics are ongoing areas of research. Impedance spectroscopy and state of charge monitoring are crucial for assessing battery health. Anode materials, such as lithium cobalt oxide (LCO), are being replaced with alternatives like lithium nickel manganese cobalt oxide (NMC) to improve capacity fade and ion transport. Thermal management and lithium extraction are critical for battery degradation mitigation.

Cobalt mining remains a concern, prompting a shift towards nickel manganese cobalt batteries and alternative cathode materials like lithium nickel manganese aluminum (NCA) and lithium nickel manganese high nickel (NCAH). In the electric vehicle (EV) sector, NMC batteries dominate, accounting for 60% of the market share. The EV market is projected to grow by 25% by 2025, driven by advancements in battery technology and government incentives. The energy storage market is expected to ex

The size of the Data Center Lithium-ion Battery market was valued at USD 506 million in 2023 and is projected to reach USD 973.57 million by 2032, with an expected CAGR of 9.8% during the forecast period.

Battery Analytics Platform Market Outlook

According to our latest research, the global Battery Analytics Platform market size reached USD 2.18 billion in 2024, demonstrating robust momentum in digital transformation across energy and mobility sectors. The market is set to expand at a CAGR of 19.7% from 2025 to 2033, reaching a projected value of USD 10.71 billion by 2033. This remarkable growth is primarily driven by the surging adoption of electric vehicles, renewable energy integration, and the escalating need for predictive maintenance and battery optimization across industries.

The primary growth factor propelling the Battery Analytics Platform market is the exponential rise in electric vehicle (EV) adoption worldwide. As governments and automakers accelerate the transition to sustainable mobility, the demand for advanced battery management systems has intensified. Battery analytics platforms are crucial for monitoring battery health, predicting failures, and optimizing performance, especially as EVs become mainstream. These platforms leverage machine learning and real-time data analytics to extend battery lifespan, reduce operational costs, and enhance safety, making them indispensable for automotive OEMs, fleet managers, and charging infrastructure providers. The increasing complexity of battery chemistries and the need for precise data-driven insights further fuel the integration of analytics solutions in the automotive sector.

Another significant growth driver is the rapid expansion of renewable energy storage systems. As solar and wind installations proliferate, grid operators and energy utilities face challenges in managing distributed energy resources and ensuring grid stability. Battery analytics platforms play a pivotal role in monitoring the performance of large-scale energy storage systems, predicting degradation, and maximizing return on investment. These platforms enable utilities to optimize charge-discharge cycles, prevent unplanned downtimes, and comply with stringent regulatory requirements. The push for decarbonization, coupled with government incentives for energy storage deployment, is accelerating the adoption of battery analytics solutions in the energy and utilities sector, fostering market expansion.

The proliferation of connected devices and the Internet of Things (IoT) in consumer electronics and industrial applications is also driving market growth. From smartphones and laptops to industrial robots and backup power systems, batteries are integral to device reliability and user experience. Battery analytics platforms empower manufacturers and enterprises to monitor device performance remotely, predict battery failures, and deliver proactive maintenance. The integration of AI-powered analytics enables real-time insights, reducing downtime and enhancing customer satisfaction. This trend is particularly prominent in mission-critical industries such as healthcare and manufacturing, where uninterrupted power is essential. As digital transformation initiatives gain traction, the demand for advanced battery analytics is expected to surge across diverse end-user segments.

Regionally, the Asia Pacific market is emerging as the global leader, accounting for the largest share of the Battery Analytics Platform market. This dominance is attributed to the region’s strong manufacturing base, rapid urbanization, and aggressive government policies promoting electric mobility and renewable energy. Countries like China, Japan, and South Korea are at the forefront of battery technology innovation and adoption. North America and Europe are also witnessing substantial growth, driven by stringent emission regulations, robust R&D investments, and the presence of leading automotive and energy companies. The Middle East & Africa and Latin America, while still nascent, are expected to experience accelerated growth due to increasing infrastructure investments and the gradual shift toward sustainable energy solutions.

Component Analysis

The Battery Analytics Platform market is segmented by component into software and services, each playing a distinctive role in the ecosystem. The software segment holds the largest market share, driven by the increasing integration of advanced analytics, artificial intelligence, and machine learning algorithms for battery management. These software solutions offer real-time monitoring, predictive analytics, and performance optimization, enabling users to extend battery lifespan and

Battery Cell Analytics Platform Market Outlook

According to our latest research, the global battery cell analytics platform market size reached USD 1.73 billion in 2024, driven by the rapid adoption of electric vehicles and advancements in energy storage technologies. The market is projected to expand at a robust CAGR of 21.2% from 2025 to 2033, reaching a forecasted value of USD 11.36 billion by 2033. This significant growth is attributed to increasing investments in battery technologies, the proliferation of smart devices, and the urgent need for real-time monitoring and predictive analytics to maximize battery performance and lifespan.

A key growth factor for the battery cell analytics platform market is the surging demand for electric vehicles (EVs) worldwide. As governments and consumers alike prioritize sustainable transportation, the automotive industry is undergoing a paradigm shift toward electrification. This transition requires advanced analytics platforms capable of monitoring battery health, predicting failures, and optimizing energy usage. The integration of artificial intelligence and machine learning into these platforms enables real-time data analysis, which enhances battery reliability and safety—critical factors for both manufacturers and end-users. Furthermore, regulatory mandates for battery safety and environmental compliance are prompting OEMs to invest heavily in analytics solutions, ensuring both operational efficiency and adherence to evolving standards.

Another significant driver is the proliferation of energy storage systems across commercial, industrial, and residential sectors. As renewable energy sources like solar and wind become increasingly prevalent, the need for efficient energy storage solutions intensifies. Battery cell analytics platforms play a pivotal role in managing and optimizing large-scale battery storage installations, enabling operators to balance energy loads, predict maintenance needs, and reduce downtime. These platforms facilitate the integration of distributed energy resources into smart grids, thereby supporting grid stability and resilience. The continuous evolution of Internet of Things (IoT) technologies further strengthens this market, as connected sensors and devices generate vast volumes of data that require sophisticated analytics for actionable insights.

The consumer electronics sector also contributes significantly to market expansion, as device manufacturers seek to differentiate their offerings through enhanced battery performance and user experience. Smartphones, laptops, wearables, and other portable devices rely on high-performance batteries, making analytics platforms indispensable for monitoring usage patterns, optimizing charging cycles, and extending product lifespans. The increasing consumer demand for longer-lasting and safer devices is compelling electronics manufacturers to integrate advanced battery analytics solutions into their product ecosystems. Additionally, the trend towards smart homes and connected devices is amplifying the need for robust battery management systems, further fueling market growth.

From a regional perspective, Asia Pacific dominates the battery cell analytics platform market, accounting for the largest revenue share in 2024. The region’s leadership is underpinned by its status as a global manufacturing hub for batteries and electronics, as well as the rapid adoption of EVs in countries such as China, Japan, and South Korea. North America and Europe are also witnessing strong growth, propelled by substantial investments in green technologies, supportive regulatory frameworks, and the presence of leading technology innovators. Meanwhile, emerging markets in Latin America and the Middle East & Africa are gradually embracing battery analytics platforms, spurred by infrastructure modernization and the expansion of renewable energy projects.

Component Analysis

The battery cell analytics platform market is segmented by component into software, hardware, and services, each playing a crucial role in the overall ecosystem. The sof

Battery Analytics Software Market Outlook

According to our latest research, the global battery analytics software market size reached USD 1.32 billion in 2024, reflecting robust demand across multiple sectors. The market is experiencing rapid expansion, with a projected CAGR of 18.7% from 2025 to 2033. By 2033, the battery analytics software market is forecasted to achieve a value of USD 6.56 billion. This impressive growth is primarily driven by the accelerating adoption of electric vehicles (EVs), the proliferation of energy storage systems, and increasing reliance on advanced battery management solutions to optimize performance and lifespan.

The primary growth factor for the battery analytics software market is the surging global shift toward electrification, particularly in the transportation and energy sectors. Governments and regulatory bodies worldwide are implementing stringent emission standards and offering lucrative incentives to promote the adoption of EVs and renewable energy sources. This transition necessitates efficient battery management, propelling demand for sophisticated analytics software capable of monitoring, predicting, and optimizing battery health and performance. As organizations seek to maximize the return on investment in battery assets, advanced analytics solutions are becoming integral to operational strategies, driving sustained market growth.

Another significant driver is the increasing complexity and scale of battery systems deployed in diverse applications. Modern batteries, especially those used in grid-scale energy storage and high-performance EVs, require real-time monitoring and predictive analytics to prevent failures, ensure safety, and extend operational life. Battery analytics software leverages artificial intelligence, machine learning, and big data capabilities to deliver actionable insights, enabling proactive maintenance and efficient energy management. This technological evolution is fostering a paradigm shift in how enterprises manage their battery assets, fueling the adoption of analytics platforms across industries.

Moreover, the rapid digital transformation and integration of Internet of Things (IoT) technologies in battery-powered devices are contributing to the expansion of the battery analytics software market. IoT-enabled sensors and cloud connectivity allow for continuous data collection and remote monitoring, facilitating seamless integration with analytics platforms. This trend is particularly pronounced in the consumer electronics and industrial sectors, where reliability, safety, and efficiency are paramount. As organizations increasingly recognize the value of data-driven decision-making, the demand for battery analytics software is expected to witness sustained momentum throughout the forecast period.

Regionally, Asia Pacific dominates the battery analytics software market, accounting for the largest share in 2024, followed by North America and Europe. The Asia Pacific region benefits from a massive EV manufacturing base, substantial investments in renewable energy, and a vibrant consumer electronics industry. North America and Europe are also witnessing rapid growth, driven by technological innovation, regulatory support for clean energy initiatives, and a strong focus on sustainability. The Middle East & Africa and Latin America, while smaller in comparison, are emerging as promising markets due to increasing adoption of energy storage solutions and smart grid technologies.

Component Analysis

The battery analytics software market is segmented by component into software and services, each playing a pivotal role in the ecosystem. The software segment encompasses advanced platforms and applications designed to monitor, analyze, and optimize battery performance in real time. These solutions integrate cutting-edge technologies such as artificial intelligence, machine learning, and big data analytics to provide comprehensive insights into battery health, usage patterns, and predictive maintenance requirements. The growing emphasis on maximizing battery efficiency, reducing operational costs, and ensuring safety is driving widespread adoption of battery analytics software across multiple industries.

On the other hand, the services segment includes consulting, integration, deployment, training, and support services that complement software solutions. As battery analytics platforms become more sophist

Data and simulation files of the paper “Parameter Estimation of an Electrochemistry-based Lithium-ion Battery Model using a Two-Step Procedure and a Parameter Sensitivity Analysis” by N. Jin, D. Danilov, P.M.J. van den Hof and M.C.F. Donkers. Simulation files can be used using Matlab 2017a. The instruction.docx in this data set contains an explanation of the folders and files used, and refers to several sections of the paper . Parts of the m-files are re-used from “Lu J. Development of fast one-dimensional model for prediction of coupled electrochemical/thermal behavior of Lithium-ion batteries. Bachelor’s thesis, The Ohio State University; 2013.” The model produces the following outputs: solid concentration, electrolyte concentration, electrolyte potential, solid potential, surface concentration in solid phase and terminal voltage.

In recent years, in-depth analysis of the manifold properties of commercial lithium-ion batteries has gained increasing attention, as it fosters optimized design and operational strategies of battery-powered applications such as battery electric vehicles. However, various properties are not easily accessible and experimental determination requires intensive efforts in the battery lab. In this study, we have performed a tear-downanalysis of a commercially available lithium-ion cell with a silicon-doped graphite anode and a Ni-rich NCA cathode. Enhanced by computed tomography (CT) scans, we reveal the cell’s internal geometrical properties. Furthermore, mini pouch half cells of the anode and cathode have been built to examine their electrochemical properties in context with full cell measurements. In particular, we examined the open circuit voltage with different measurement methods and for different temperatures and performed reconstruction of the full cell via fitting of electrode potentials. We give detailed insights into the kinetics of the cell by analyzing the distribution of relaxation times (DRT) calculated from electrochemical impedance spectroscopy (EIS). Individual loss processes are assigned to either electrode and their polarization resistances and time constants are quantified over a large SOC and temperature range. A comprehensive open-source dataset of the investigated cell is provided to propel international research activities in the development of advanced models and algorithms forlithium-ion batteries.

The Battery Market report segments the industry into Type (Primary Batteries, Secondary Batteries), Technology (Lead-acid Battery, Lithium-ion Battery, Nickel-metal Hydride (NiMH) Battery, and more), Application (Automotive Batteries (HEV, PHEV, and EV), Industrial Batteries (Motive, Stationary (Telecom, UPS, ESS)), and more), and Geography (North America, Asia-Pacific, and more).

Battery Health Analytics Market Outlook

According to our latest research, the global Battery Health Analytics market size reached USD 2.1 billion in 2024, driven by the surging demand for advanced battery monitoring and predictive maintenance solutions across various industries. The market is experiencing robust momentum, registering a CAGR of 18.7% from 2025 to 2033. By 2033, the global Battery Health Analytics market is forecasted to surpass USD 10.8 billion, underpinned by the rapid adoption of electric vehicles, growth in renewable energy storage, and increasing reliance on battery-powered devices. The market’s growth is further propelled by technological advancements in analytics platforms and the integration of artificial intelligence and machine learning for real-time battery diagnostics.

The primary growth driver for the Battery Health Analytics market is the exponential rise in the deployment of batteries across critical sectors, particularly in electric vehicles and renewable energy storage systems. As global economies accelerate their shift towards electrification and sustainability, the need for reliable battery performance and longevity has become paramount. Battery Health Analytics solutions offer real-time insights into battery state-of-health, state-of-charge, and predictive failure analysis, enabling organizations to optimize maintenance schedules, reduce downtime, and extend asset lifespans. The integration of IoT sensors and cloud-based analytics platforms has further enhanced the ability to collect, process, and act upon vast amounts of battery data, thereby fueling market expansion.

Another significant growth factor is the increasing regulatory emphasis on safety, efficiency, and environmental compliance in battery usage. Governments and industry bodies worldwide are introducing stringent mandates for battery management, especially in sectors such as automotive, aerospace, and energy utilities. These regulations necessitate advanced analytics tools to ensure compliance, mitigate risks of battery failures, and reduce hazardous waste. Furthermore, the proliferation of consumer electronics and the need for uninterrupted power supply in industrial and critical infrastructure settings have intensified the demand for sophisticated battery monitoring and analytics solutions, driving market growth across diverse verticals.

Technological innovation remains a cornerstone of market growth, with advancements in artificial intelligence, machine learning, and big data analytics revolutionizing the capabilities of Battery Health Analytics platforms. Companies are investing heavily in R&D to develop predictive maintenance algorithms, anomaly detection systems, and automated reporting tools that can proactively identify potential battery issues before they escalate. The convergence of edge computing and cloud technologies has enabled scalable, cost-effective deployment models, making advanced analytics accessible to both large enterprises and small-to-medium businesses. This democratization of technology is expected to broaden the market’s reach and accelerate adoption rates globally.

From a regional perspective, Asia Pacific continues to dominate the Battery Health Analytics market, accounting for the largest share in 2024, driven by the rapid expansion of electric vehicle manufacturing, significant investments in renewable energy, and the presence of leading battery producers in countries such as China, Japan, and South Korea. North America and Europe are also witnessing substantial growth, fueled by robust R&D activities, supportive regulatory frameworks, and increasing adoption of battery-powered solutions in automotive, industrial, and consumer sectors. Meanwhile, emerging markets in Latin America and the Middle East & Africa are gradually embracing battery analytics technologies, supported by infrastructure modernization initiatives and growing awareness of the benefits of proactive battery management.

Component Analysis

The Battery Health Analytics market by component is segmented into software, hardware, and services, each playing a pivotal role in the overall ecosystem. Software solutions are at the forefront, enabling the collection, aggregation, and analysis of battery performance data through advanced algorithms and user-friendly dashboards. These platforms leverage machine learning and artificial intelligence to provide actionable insights, predictive maintenance alerts, and comprehensive reporting functionalities. As the complexity of bat

The UPS Battery for Data Center market is booming, projected to reach $5.64 billion in 2025, with a CAGR of 6.59% through 2033. Driven by cloud computing and IoT growth, this report analyzes market trends, key players (Eaton, Schneider Electric, EnerSys), and the shift towards lithium-ion batteries. Discover insights into regional market share and future growth potential.

Micromobility Battery Analytics Market Outlook

According to our latest research, the global Micromobility Battery Analytics market size reached USD 1.12 billion in 2024, and it is expected to grow at a robust CAGR of 19.4% from 2025 to 2033, reaching a forecasted value of USD 5.47 billion by 2033. This impressive growth trajectory is primarily fueled by the accelerating adoption of micromobility solutions in urban centers, the rising demand for efficient battery management, and technological advancements in analytics platforms. The market’s expansion is underpinned by the increasing integration of data-driven insights into fleet operations, which is enabling operators and private owners to optimize battery life, reduce operational costs, and enhance user experience.

One of the key growth factors driving the Micromobility Battery Analytics market is the rapid urbanization and congestion in major cities worldwide. Urban populations are increasingly turning to micromobility solutions such as e-scooters, e-bikes, and e-mopeds to address last-mile connectivity challenges and reduce reliance on traditional automobiles. This shift is generating a massive volume of battery usage data, which, when analyzed, can reveal critical insights into battery performance, degradation patterns, and usage trends. As cities invest in smart infrastructure and promote sustainable transportation, the demand for advanced analytics platforms that can monitor, predict, and optimize battery health is surging, empowering both shared mobility operators and private owners to maximize the value of their electric fleets.

Technological innovation represents another significant growth driver for the Micromobility Battery Analytics market. The proliferation of IoT sensors, real-time data collection, and cloud-based analytics platforms has revolutionized how battery data is captured, stored, and analyzed. Advanced algorithms and machine learning models are now capable of delivering predictive maintenance insights, identifying potential battery failures before they occur, and recommending optimal charging cycles. These capabilities not only extend battery lifespan but also reduce unexpected downtime, improve safety, and lower total cost of ownership. As battery technologies evolve, particularly with the widespread adoption of lithium-ion and emerging solid-state batteries, analytics solutions are becoming indispensable for ensuring operational efficiency and sustainability in micromobility fleets.

Regulatory support and environmental sustainability are also catalyzing the growth of the Micromobility Battery Analytics market. Governments across North America, Europe, and Asia Pacific are implementing policies to reduce urban emissions and promote the use of electric vehicles, including micromobility options. Subsidies, tax incentives, and investments in charging infrastructure are encouraging both individuals and fleet operators to adopt electric micromobility vehicles. At the same time, there is increasing scrutiny on battery disposal and recycling, making it crucial to monitor battery health and optimize usage to minimize environmental impact. Analytics platforms play a vital role in ensuring compliance with regulatory standards, enhancing battery lifecycle management, and supporting the transition to greener urban mobility systems.

Regionally, Asia Pacific dominates the Micromobility Battery Analytics market due to its large urban populations, rapid adoption of electric micromobility vehicles, and strong presence of leading battery manufacturers. China, in particular, is a global leader in the production and deployment of e-bikes and e-scooters, driving demand for sophisticated battery analytics solutions. North America and Europe are also significant markets, with robust investments in smart city initiatives and stringent environmental regulations fostering the integration of analytics into micromobility operations. Latin America and the Middle East & Africa are emerging as promising regions, with growing urbanization and increasing interest in sustainable transportation solutions. As these regions continue to invest in infrastructure and technology, the market for micromobility battery analytics is expected to expand further, offering substantial growth opportunities for industry stakeholders.

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Battery Market Size 2024-2028

The battery market size is valued to increase USD 296.6 billion, at a CAGR of 18.69% from 2023 to 2028. Shift in the automotive industry to EVs will drive the battery market.

Major Market Trends & Insights

APAC dominated the market and accounted for a 44% growth during the forecast period.
By Application - Portable batteries segment was valued at USD 52.10 billion in 2022
By Type - Lithium ion segment accounted for the largest market revenue share in 2022

Market Size & Forecast

Market Opportunities: USD 291.34 billion
Market Future Opportunities: USD 296.60 billion
CAGR : 18.69%
APAC: Largest market in 2022

Market Summary

The market encompasses the production, sales, and installation of various battery types, primarily driven by the shift towards renewable energy and the surge in electric vehicles (EVs) adoption. Core technologies, such as lithium-ion and nickel-metal hydride, dominate the landscape, with lithium-ion batteries holding a significant market share due to their high energy density and long cycle life. Applications span across industries, including telecommunications, grid energy storage, and transportation, with the automotive sector experiencing a major transformation. Technological developments, such as solid-state batteries and advanced battery management systems, are pushing the boundaries of energy storage capabilities.
However, challenges persist, including the use of counterfeit batteries and regulatory compliance. According to a recent study, The market is projected to reach a 30% market share in the EV sector by 2025, underscoring the market's continuous evolution and growth potential.

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

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How is the Battery Market Segmented and what are the key trends of market segmentation?

The battery industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD billion' for the period 2024-2028, as well as historical data from 2018-2022 for the following segments.

Application

  Portable batteries
  Automotive batteries
  Industrial batteries
  Energy Storage Systems (ESS)
  Aerospace and Defense
  Wearables


Type

  Lithium ion
  Silicon-Graphite Composite
  Pure Silicon Anode
  Silicon-Based Solid-State Batteries
  Silicon-Sulfur
  Others


Technology

  Primary Batteries
  Secondary (Rechargeable) Batteries


End-User

  Automotive
  Electronics
  Utilities
  Industrial
  Healthcare


Geography

  North America

    US
    Canada


  Europe

    Germany
    UK


  Middle East and Africa

    UAE


  APAC

    China
    India
    Japan
    South Korea


  South America

    Brazil


  Rest of World (ROW)

By Application Insights

The portable batteries segment is estimated to witness significant growth during the forecast period.

The rechargeable the market, specifically lithium-ion batteries, is experiencing significant growth, driven primarily by the automotive sector. Currently, adoption in this segment has risen by 25%, with electric vehicles (EVs) and e-bikes leading the charge. This trend is expected to continue, with industry forecasts projecting a 27% increase in demand for these batteries over the next few years. Lithium-ion batteries offer several advantages over traditional chemistries, such as higher energy density, improved performance, longer cycle life, and lower production costs. These factors make lithium-ion batteries an attractive choice for EV manufacturers like Tesla, leading to increased market penetration.

Battery technology has advanced significantly, with enhancements in cell balancing, power electronics, and thermal management. Fast charging capabilities, self-discharge rate reduction, and improved energy efficiency are essential features that have become increasingly important for battery users. Material science plays a crucial role in battery development, with anode and cathode materials undergoing continuous research and innovation. Battery testing, including impedance spectroscopy and discharge curves, is essential to assess battery health and performance. Battery pack design, capacity fade, specific power, and cycle life are critical factors that influence battery selection and application. Solid-state batteries and battery management systems are emerging technologies that aim to address challenges such as internal resistance and state of health monitoring.

Battery recycling is another area of focus, as the industry seeks to minimize environmental impact and maximize resource utilization. The ongoing evolution of battery technology and its applications across various sectors underscores the dynamic nature of this market.

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The Portable batteries segment was valued at USD 52.10