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Shivanshu Shrivastava,
Chhagan Charan,
- Student, School Of VLSI AND EMBEDDED SYSTEM, National Institute Of Kurukshetra, Haryana, India
- Assitant Professor, Department of ECE National Institute of Technology Kurukshetra, Haryana, India
Abstract
The perception of electric cars (EVs) as a strong alternative to for internal combustion engine automobiles is growing. For electric vehicle (EV) technologies to advance, they must develop quickly, especially in the area of battery technology. light weight, increased energy capacity, quick charging times, lithium-ion (Li-ion) batteries are generally used for electric vehicles (EVs). The efficiency of the battery management system (BMS) and battery performance are critical elements influencing electric vehicle (EV) performance. In order to maximize battery performance, guarantee safety, and extend battery life, the BMS is essential. It is intended to tackle issues including controlling energy use, cutting down on heating time at low temperatures, and precisely forecasting battery behavior. Both battery performance and the effectiveness of the Battery Management System (BMS) have a significant impact on the performance of electric vehicles. In order to maximize battery performance, maintain operating safety, and increase battery lifespan, the BMS is essential. It tackles important issues including energy management, cutting down on heating time in cold weather, and precisely forecasting battery behavior in a range of operational scenarios. Battery state estimate is necessary for efficient energy management and vehicle control. Although Li-ion technology is ideal for (EVs), their intrinsic instability makes it difficult to precisely estimate metrics such as state of charge (SOC). Thus, creating a precise and dependable BMS is essential for efficiently controlling Li-ion batteries and guaranteeing the dependability and safety of EV operations. A examination of methodologies such as battery modeling, state estimate, and prediction provides useful insights into the current state of EV technology and identifies opportunities for improvement.
Keywords: Battery Management System, Lithium-ion Battery, State of Charge (SOC) State of Health (SOH), State of Power (SOP), Cmax Cr, AEKF, EKF, State Of Life (SOL)
Shivanshu Shrivastava, Chhagan Charan. Review of Battery Management System and SOC. Journal of VLSI Design Tools and Technology. 2026; 16(01):-.
Shivanshu Shrivastava, Chhagan Charan. Review of Battery Management System and SOC. Journal of VLSI Design Tools and Technology. 2026; 16(01):-. Available from: https://journals.stmjournals.com/jovdtt/article=2026/view=238908
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Journal of VLSI Design Tools and Technology
| Volume | 16 |
| 01 | |
| Received | 28/06/2025 |
| Accepted | 10/02/2026 |
| Published | 20/03/2026 |
| Publication Time | 265 Days |
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