Mathematical modeling and optimization of the active suspension system of a 6x6 electric vehicle

Abstract

Vehicle suspension systems have a significant role in the capacity of transmit forces coming from the road and in vehicle performance. Loads between the road and the vehicle body significantly affect driver health, comfort, and vehicle drive features. Some research shows that the quality of suspension systems is of great importance in vehicle accident rates. The suspension system also affects roadholding significantly. In this study, mathematical modeling was performed for a vehicle with a 6 x 6 in-wheel electric motor. A free body diagram was generated for the system and the wheels, vehicle body, seat, human model, and in-wheel electric motors were addressed in the mathematical simulation modeling. "Bump type" and "Random type" road model scenarios as road inputs were created. In the mathematical model, simulations of models with passive and active suspension systems were carried out and system accuracy was confirmed. Three different methods were used for optimization: Genetic Algorithm (GA), Particle Swarm Optimization (PSE) and Differential Evolution (DE) Optimization. The stiffness and damping coefficients of the wheel suspension, the coefficients of the active suspension controllers, the stiffness and damping coefficients of the seat suspension and the suspension of wheel-mounted motors are selected as design variables of the optimization problem. The optimizations were made separately and compared for two different road scenarios. According to the ISO 2631-1 Health Guide standard, it was evaluated which system is more efficient in terms of its effects on human health and comfort. ISO 2631-1, which defines vibration exposure limits, has been used to calculate driver health limits. Optimization results with active suspension systems showed better improvement compared with the simulations performed with passive suspension systems. Moreover, optimization results especially in systems used for a long time demonstrate greater results on human health.