**5. Conclusions**

This chapter introduces a method for tracking the state of charge (SOC) using a fuzzy-tuned model predictive controller. The mathematical models for the components of an electric vehicle traction system were developed and tested on Simulink. The simulation was conducted using the New European Drive Cycle, during which the motor speed and battery SOC were continuously monitored. The outcomes of the simulation demonstrate the effectiveness of the SOC tracking technique in regulating motor speed when there are no SOC restrictions. Furthermore, it successfully maintains the battery SOC within the defined maximum permitted value, albeit with some trade-offs in motor speed tracking performance. The absolute average deviation from the reference for the SOC tracking technique was lower than the Fuzzy A-ECMS, and A-ECMS techniques which yielded 0.00095, 0.0019, and 0.0037, respectively. However, the ECMS technique with a fixed optimal equivalent factor had the lowest deviation of 0.0003. In other words, there is still room for improvement in the SOC tracking technique. Furthermore, the robustness of the technique on different driving behaviors is yet to be tested. In summary, the simulation results provide substantial evidence supporting the effectiveness of the SOC tracking technique.

Future research directions include:

