Control And Multi-Objective Optimization Of Active Energy-Regeneration Suspension Based On Road Estimation

The vehicle suspension system is an important part of chassis system,whose main function is to reduce body vibration and improve driving safety and comfort.Compared with traditional passive suspension,active suspension can significantly improve the ride comfort and handling stability of the vehicle,to achieve the best dynamic performance of vehicles under different road conditions,which is one of the main research issues for smart electric vehicles in the future.In view of the problem that some problems existing in current suspension control research,this paper is based on the nonlinear suspension system,to study the non-linear control of the active suspension and the energy regeneration characteristics of the suspension combined with the road estimation algorithm.The main work is as follows:Firstly,considering the damping nonlinearity and spring stiffness nonlinearity of a two-degree-of-freedom suspension model,a polynomial response surface method is used to establish a dynamic model of the nonlinear suspension.Based on this nonlinear model,a fuzzy neural network algorithm is used to establish active suspension reverse recognition system to recognize the current road level through the suspension dynamic response.Secondly,in view of the non-linear characteristics of the suspension model,sliding mode control is used to control the active suspension.In consideration of the actual fuel consumption and difference of the passengers’ number,the sprung mass has an uncertainty during the driving process of the actual vehicle.Therefore,this paper designs an adaptive sliding mode controller based on sliding mode control to eliminate the influence of the uncertain of the sprung mass on the control effect of the controller.Then,the characteristics of electromagnetic active suspension energy reclaiming and its switching control strategy are researched,and the energy regeneration circuit of electromagnetic active suspension is designed.Taking into account the difference of driver ’s requirements for comfort,safety and energy saving under different road levels,this paper designs an energy-regeneration switching strategy of electromagnetic active suspension based on road recognition.Considering the contradiction between safety,comfort and energy saving of the electromagnetic suspension,the controller parameters and suspension structure parameters were optimized using Multi-Objective Particle Swarm Optimization(MOPSO)to design the performance of suspension dynamics and the ability of energy regenerative,and the optimal solution was selected by fuzzy set theory from the Pareto optimal solutions.Simulations demonstrate that the optimized adaptive slide controller can better coordinate the energy reclaiming characteristics of the suspension and the vibration reduction characteristics,and achieve the comprehensive optimal safety,comfort and energy saving of the electromagnetic suspension at different road levels.Finally,by establishing a seven-degree-of-freedom model of the vehicle and an objective function,different road conditions are designed to verify the accuracy and effectiveness of the adaptive sliding control of the active suspension based on the road estimation algorithm in the vehicle control.In view of the problems of road estimation algorithms,a road estimation algorithm scheme for intelligent connected cars based on V2X and edge cloud technology is designed.