A Fuzzy Logic Based Evaluation of Electric Vehicle Battery State of Charge and State of Health in a Regenerative Braking State

Abstract This paper focused on developing a fuzzy logic-based control system that dynamically regulated energy recovery during regenerative braking. An optimal charging condition with minimized battery degradation during acceleration and braking processes were illustrated. The proposed model employed three key inputs that involved braking force, motor speed, and state of charge of lithium-ion battery with an output that depicted the charging and discharging current. Fuzzy Logic Controller demonstrated superior adaptability and robustness in handling dynamic braking situations for energy recovery enhancement and battery longevity. Using triangular, trapezoidal and Gaussian membership functions within a Mamdani inference system and centroid defuzzification, fuzzy surfaces were generated to estimate SOH degradation and drift in SOC. Simulation results showed that SOH degradation ranged from 0.30 to 0.85 pu, with a mean value of 0.489 pu and a standard deviation of ±0.221 pu. The steepest degradation occurred at 20% SOC with Capacity rate of four (4C) under a highway braking process. Conversely, At 80% SOC, the state of health degradation remained lowest while maintaining 0.44 pu for highway drive, 0.39 pu for suburban and 0.31 pu for city drive conditions. Appreciable thermal acceleration was achieved after 450 C. A drift error of 0.86 p.u was realized under frequent braking.