Multi-objective optimization design of in-wheel motors drive electric vehicle suspensions for improving handling stability

In-wheel motor drive electric vehicle has superior dynamic control capability, but the inner space of wheel hubs that are originally used to install the suspensions is occupied by wheel motors, which leads to an increase in unspring mass and a structural change in suspensions. By referring to a standard car’s suspension to design the suspensions of an in-wheel motor drive electric vehicle, the required vehicle handling stability is hard to reach, so the structure of the suspensions must be redesigned and optimized to facilitate the next step of vehicle dynamics control. In this paper, the virtual prototype is established based on a self-developed in-wheel motor drive electric vehicle, and the correctness of the model is validated by field tests. Then, the design of experiment method is used to analyze the impact of the structural parameters of the front double pivot suspensions and the rear double wishbone suspensions; the sensitivity of the suspension parameters is obtained by entropy measurement, and the suspension parameters with great influence on the handling stability are selected as the design variables and optimized by Non-dominated Sorting Genetic Algorithm II. Through the optimization, the maximum lateral acceleration and the maximum roll angle can be reduced by 4.8% and 10.3%, respectively, under the double lane change test and reduced by 12.7% and 7.9%, respectively, under the serpentine test. The maximum speeds under double lane change and serpentine test simulations can be increased by at least 7% and 5%, respectively. The related research has guiding significance for the suspension design of the in-wheel motor drive electric vehicles.