Optimizing energy efficiency in battery-powered electric vehicles: Leveraging Pontryagin’s minimum principle and model adaptive control

Electric vehicles, or EVs, are gaining more attention than ever before as a potential replacement for conventional vehicles. However, energy management has always been the primary and crucial concern in controlling EVs due to the current restricted energy density of batteries. This manuscript presents a Model Adaptive Control (MAC) utilizing Pontryagin’s Minimum Principle (PMP) to enhance the efficiency of electric vehicles (EVs) and introduces a structured continuous energy management approach through system development. The proposed method, named PMP-MAC, incorporates a Savitzky-Golay filter and the Erode-Gobichettipalayam smoother driving cycle to refine the control process. The major objective of the proposed approach is to enhance motor efficiency and improve the driving performance of electric vehicles. The MAC is used to control the reference current signal for regulating motor speed, while PMP is employed to solve energy efficiency problems. On the MATLAB platform, the proposed MAC is assessed and contrasted with other existing techniques. The proposed method shows better results in all existing such as Dynamic programming (DP), PMP, and Adaptive Optimization Control (AOC). The proposed method attains an efficiency of 95.23%, a total cost of 151.2 INR, and a computation time of 0.012s. The proposed PMP-MAC achieves better results compared to other existing methods.