1. Multi-body Dynamics Modelling of EV Prototype An EV prototype, with all the wheels independently driven by 4 in-wheel motors, is developed. In cooperation with Shanghai Motor Vehicle Inspection Center, the prototype undergoes a series of practical measurements and road tests. Based on the obtained vehicle parameters, a multi-body dynamics model is built by using SolidWorks and Adams/Car, and then validated by track test data. The virtual prototype is served as the control plant in simulation. 2. Adaptive FO-PID Controller Design In order to enhance the handling and stability performance of the EV, an adaptive FO-PID controller is designed. Considering the model uncertainties, e.g. changes in body mass and yaw inertial resulted from changed mass distribution, a Parameter Self-Adjusting Differential Evolution (PSA-DE) algorithm is adopted for tuning the controller parameters, i.e. Kp, Ki, Kd, λ and μ. As a modification of traditional DE algorithm, the so-called Variance of Population’s Fitness is utilized to evaluate the iteration result. In order to avoid the premature convergence problem, a random disturbance is applied on the scaling factor in each iteration step, until the optimal solution is resolved. 3. Simulation and Analysis Simulations are carried out to examine the effectiveness of the proposed controller for the EV. The vehicle performances, respectively with and without the controller, are compared in different cases. The results will be presented and analyzed in the full paper in detail. 4. Conclusions Based on a particular EV prototype, a multi-body dynamics model is built in Adams/Car, and validated via track test data. An adaptive FO-PID controller, with its parameters tuned by PSA-DE algorithm, is proposed to enhance the vehicle handling and stability performances. Simulations are carried out, and the effectiveness of the proposed controller is verified through the comparison between the EV with/without controller.