基于RBF与粒子群优化算法的电子油门踏板电压调节参数的优化设计

The optimization design for accelerator pedal module's voltage parameter based on RBFN and PSO

针对汽车电子油门踏板在装配过程中电压调节参数值不准确,而影响产品使用性能的问题,提出采用RBF神经网络建立怠速点电压、机械止点电压及Kick-down初始受力电压参数网络数学模型,运用粒子群优化算法对怠速点电压或机械止点电压的取值进行优化,寻求电压调节的最优值。通过该方法,改善了产品电压位移的特性,提高了产品使用性能,为汽车智能化控制提供了支持。

Aimed at the uncertainty of voltage parameter adjusting in the APM assembling process and production＇s function problem,it put forth applying the RBFN to construct the parameter mathematic model and utilizing the Particle Swarm optimizer to optimize the idle and mechanical stop position＇s voltage parameter-value.It can improve the production voltage-way relation and production function,offer basis for the automotive intelligence control.