Hardware-in-loop setup for SoC estimation of Lithium-ion batteries using Simulink Desktop Real Time

Battery management systems (BMS) are protective circuits used to maintain the safe operation of the battery under all working conditions. The BMS also helps in cell balancing by bleeding off excess energy from high cells to bring all the cells down to the same state of charge (SoC). Evaluation of the short-term and long-term performance of a BMS is difficult, as it requires connecting it to a physical high-voltage battery, which is expensive and potentially unsafe. Additionally, it’s worth noting that the voltage of a Lithium-ion battery increases as the number of series connected cells increases. In the work presented here, Hardware-in-the-loop testing is performed on the BMS Electronic Control Unit (ECU), which has a lot more advantages than direct testing. Lithium-ion batteries are modeled in Simulink, which outputs signals exactly as compared to a real plant to test the faults occurring in the batteries. The controller model (SoC estimation algorithm) is also modeled in Simulink to perform Model-in-loop tests, followed by Software-in-loop and Processorin-loop. Finally, the SoC estimation algorithm using Extended Kalman Filter (EKF) and Machine Learning is validated using a Hardware-in-the-loop (HIL) system and the time required to compute one iteration is compared.