Optimal control has been extensively used in vehicle’s active suspension control. However, the fixed control weighting coefficient is difficult to meet the dynamic changes in suspension performance requirements of vehicles at different speeds and road levels. This paper proposes an innovative optimal control strategy for active suspension systems with control weighting coefficient dynamically adjusted based on operating conditions, with the aim of ensuring a good ride comfort for vehicles under various operating conditions. Firstly, by using the theory of random vibration and the real integral residue theorem, the analytical calculation formulas of the performance evaluation index for optimal control active suspension systems are derived, and an effective control weighting coefficient characterization method is explored from a theoretical analysis perspective. Subsequently, an identification method of road roughness based on RIMENARX neural network and vehicle ride comfort inverse model, and a real-time adjustment method of optimal control weighting coefficient based on performance evaluation index analytical calculation are established. Then an optimal control strategy for active suspension systems with control weighting coefficient dynamically adjusted based on operating conditions is proposed. The correctness of the established method is verified through bench test. Experimental results show that the proposed optimal control strategy can significantly improve the vehicle’s ride comfort while ensuring its safety. This study provides a new idea for optimal control active suspension systems’ design.

Vehicle active suspension; Optimal control; Performance evaluation index; Analytical solution; Control strategy design