Intelligent Battery Management System

Tharun, J.; Vishnupriyan, J.; Muthumanickam, S.; Chidambarathanu, K.

doi:10.1109/icscan53069.2021.9526440

Cited by 4 publications

(1 citation statement)

References 13 publications

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“…The battery management system (BMS) is another fundament component of systems powered by batteries [3]. A BMS is an electronic circuit which prevents the battery from operating outside its safety range.…”

Section: A Motivationmentioning

confidence: 99%

SPICE Model of a Passive Battery Management System

Guran,

Florescu,

Perişoară

2024

IEEE Access

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The migration towards green energy has seen a big increase in the number of electric vehicles and energy storage systems existing on the market, where the battery is a fundamental part. In order to provide the necessary voltage and current for the power supply of the system, the battery cells are connected in series and/or in parallel. These types of connections lead to an imbalance in the cells' state-of-charge over time and drastically decrease the battery life. In order to prevent this imbalance, a battery management system must be used. At the moment, the simulation is used before the physical implementation in order to verify the system design, with SPICE being the preferred mixed-signal simulator. However, the literature focuses on the physical design and implementation of BMS without treating the SPICE simulation. For this reason, this article proposes for the first time the implementation and verification of a passive battery management system simulation model in the most used SPICE-based environment, OrCAD Capture. The BMS model consists of a modular approach, with the following blocks used in the implementation: cell voltage sensing, battery pack current sensing, cell balancing, power supply, microcontroller. Each block is simulated and verified separately and then integrated into the final BMS model. The simulation results of the final BMS model show that the system performs the balancing of the cells correctly according to the balancing algorithm, while the maximum error in the measurement of the cell voltages and battery pack current is 1.5%. Based on these results, the proposed methodology can be used in the design of real-world battery management systems to reach the best possible architecture before the physical implementation, leading to cost and time optimization.

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Section: A Motivationmentioning

confidence: 99%