Performance and Robustness Enhancement of Fractional Order Controller (FOC) for Electric Vehicles (EV) Using Intelligent Swarms.

As the impacts of global warming intensify, the automotive industry is increasingly emphasizing the development of eco-friendly vehicles with superior range and performance compared to conventional ones. Electric vehicles have emerged as a promising solution to reduce harmful emissions in the transportation sector. This study focuses on creating a nonlinear dynamic model for electric vehicles by integrating kinetic and electrical components. The key criterion in EV speed control is robustness, prompting the construction of various controllers to ensure resilience and disturbance rejection. These controllers include both traditional ones like proportional-integral-derivative (PID) and fractional order PID (FOPID) controllers. Fractional calculus has gained significant attention in control systems engineering due to the fractional orders of the integral and derivative terms, offering enhanced robustness and optimal control. This thesis employs multiple optimization strategies to design an FOPID controller, ensuring the optimal performance of a robust control system for electric vehicles. Initially, the controller is developed using intelligent swarm optimization techniques, such as particle swarm optimization (PSO) and grey wolf optimization (GWO), through simulations in MATLAB R2022b. The results demonstrate the effectiveness of PSO and GWO algorithms in reducing the objective integral of time multiplied by absolute error (ITAE) function in the speed control system utilizing an FOPID controller. The performance of a conventional PID controller is compared with that of a FOPID controller, highlighting the superiority of the GWO-FOPID strategy, presented as a novel methodology. The outcomes underscore the remarkable performance of the GWO-FOPID controller, ensuring rapid responsiveness in controlling EV speed, with a rise time of 0.008978 seconds, a settling time of 0.01 seconds, and zero absolute time error (ITAE). [ABSTRACT FROM AUTHOR]