Performance Evaluation of Battery Management Systems in Lithium-Ion Battery-Powered Electric Vehicles

Abstract

This work provides the first exhaustive quantitative assessment of Battery Management Systems (BMS) in electric vehicles (EVs). This work evaluates BMS as each attempts to establish the State of Charge (SOC) and State of Health (SOH) estimation, cell balancing, thermal control, and fault safeguarding efficiency. This work evaluates real-world scenario BMS efficiency considering different driving conditions, environmental conditions, and scenarios to age the battery pack. A substantial amount of work has been done to assess the battery pack's cell voltages, currents, temperatures, State of Charge/State of Health, and fault logs in a 48V, 60Ah lithium-ion battery pack. The work has primarily focused on measuring the SOC error, SOH drift, balancing efficiency, and thermal deviation. This work demonstrates the BMS SOC estimation efficiency of 3% error, while SOH estimation accuracy dropped by 5% after 1000 cycles of charge and discharge. BMS cell balancing works efficiently at average driving conditions; however, it becomes much less efficient with aggressive driving. The BMS thermal regulation suffered greatly in extreme heat (45°C) as the temperature regulation control was ±5°C from the ideal temperature of 5°C. Fault BMS fault detection was remarkably fast, detecting overvoltage and overcurrent conditions in less than 200 ms. This work provides a summary of important BMS efficiency bottlenecks while offering solutions to advance BMS safety, BMS longevity, and BMS powered EVs efficiency.

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