基于路面识别的主动馈能悬架多目标控制与优化

针对主动悬架减振性能和馈能特性在不同等级路面适应性较差的问题,建立了非线性电磁主动悬架模型;考虑车辆在行驶过程中悬架簧上质量存在不确定性,提出了一种主动悬架自适应滑模控制器;基于不同路面下悬架动力学响应数据,采用自适应模糊神经网络算法识别路面等级,确定控制器目标系数,实现了主动悬架安全性和舒适性之间的协调;研究了电磁主...

Multi-objective control and optimization of active energy-regenerative suspension based on road recognition

For the problem that the vibration reduction performance and energy-regenerative characteristics of active suspension are less adaptable under different road classes, a nonlinear electromagnetic active suspension model was constructed. Considering the suspension sprung mass uncertainty during vehicle driving, an adaptive sliding mode controller of active suspension was proposed. An adaptive fuzzy neural network and the dynamics data of suspension under different roads were used to recognize road classes and determine the objective coefficient of the controller. Then, the coordination between safety and comfort of active suspension was realized. The energy-regeneration characteristics and switch control strategies of electromagnetic active suspension were studied. On this basis, the suspension dynamic performance and energy-regeneration characteristic were taken as the design objectives, and the contradictory relationships between the safety, comfort, and energy efficiency of electromagnetic active suspension were considered to comprehensively optimize the controller and suspension structure parameters through the multi-objective particle swarm optimization (MOPSO). The optimal solution was acquired from the Pareto solution set after the multi-objective optimization according to the fuzzy set theory. Research result reveals that the fuzzy neural network gives a maximum recognition error within 10% for various road classes when the nonlinear electromagnetic active suspension is employed. Thus, it meets the requirement of recognition accuracy. For C-class roads, the vibration acceleration of sprung mass of optimized active suspension reduces by 35.3% compared with the traditional passive suspension. The tire dynamic displacement increases by 7.7%, but it is still within 10%, ensuring safety. Compared with the original active suspension, the optimized suspension has 10.5% less sprung mass vibration acceleration and 1.7% higher energy-regeneration efficiency. The optimized adaptive sliding mode controller can better balance the energy-regeneration and vibration reduction characteristics of suspension. The established nonlinear electromagnetic active suspension model can realize the comprehensive optimization of safety, comfort, and energy efficiency of suspension system under different road classes. 5 tabs, 9 figs, 30 refs.