The primary function of a suspension system is to isolate the vehicle body from road irregularities thus providing the ride comfort and to support the vehicle and provide stability. The suspension system has to perform conflicting requirements; hence, a passive suspension system is replaced by the active suspension system which can supply force to the system. Active suspension supplies energy to respond dynamically and achieve relative motion between body and wheel and thus improves the performance of suspension system. This study presents modelling and control optimization of a nonlinear quarter car suspension system. A mathematical model of nonlinear quarter car is developed and simulated for control and optimization in Matlab/Simulink® environment. Class C road is selected as input road condition with the vehicle traveling at 80 kmph. Active control of the suspension system is achieved using FLC and PID control actions. Instead of guessing and or trial and error method, genetic algorithm (GA)-based optimization algorithm is implemented to tune PID parameters and FLC membership functions’ range and scaling factors. The optimization function is modeled as a multi-objective problem comprising of frequency weighted RMS seat acceleration, Vibration dose value (VDV), RMS suspension space, and RMS tyre deflection. ISO 2631-1 standard is adopted to assess the ride and health criterion. The nonlinear quarter model along with the controller is modeled and simulated and optimized in a Matlab/Simulink environment. It is observed that GA-optimized FLC gives better control as compared to PID and passive suspension system. Further simulations are validated on suspension system with seat and human model. Parameters under observation are frequency-weighted RMS head acceleration, VDV at the head, crest factor, and amplitude ratios at the head and upper torso (AR_h and AR_ut). Simulation results are presented in time and frequency domain. Simulation results show that GA-based FLC and PID controller gives better ride comfort and health criterion by reducing RMS head acceleration, VDV at the head, CF, and AR_h and AR_ut over passive suspension system.

中文翻译：

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主动非线性四分之一汽车悬架系统基于遗传算法的多目标优化-PID和模糊逻辑控制

悬架系统的主要功能是使车身与道路不平整隔离，从而提供乘坐舒适性并支撑车辆并提供稳定性。悬挂系统必须执行相互矛盾的要求；因此，被动悬架系统被主动悬架系统代替，主动悬架系统可以向系统提供力。主动悬架提供能量以动态响应并实现车身与车轮之间的相对运动，从而提高了悬架系统的性能。这项研究提出了非线性四分之一汽车悬架系统的建模和控制优化。开发了非线性四分之一车的数学模型，并对其进行了仿真，以在Matlab /Simulink®环境中进行控制和优化。当车辆以80 kmph的速度行驶时，选择C类道路作为输入道路条件。悬架系统的主动控制是通过FLC和PID控制动作实现的。代替猜测和/或试错法，实现了基于遗传算法（GA）的优化算法来调整PID参数和FLC隶属函数的范围和比例因子。优化函数被建模为一个多目标问题，包括频率加权RMS座椅加速度，振动剂量值（VDV），RMS悬架空间和RMS轮胎挠度。采用ISO 2631-1标准来评估乘坐和健康标准。在Matlab / Simulink环境中，对非线性四分之一模型以及控制器进行了建模，仿真和优化。可以看出，与PID和被动悬架系统相比，GA优化的FLC可以提供更好的控制。通过座椅和人体模型对悬架系统进行了进一步的仿真验证。观察的参数是频率加权RMS头部加速度，头部VDV，波峰因数以及头部和上半身的振幅比（AR_h和AR_ut）。仿真结果显示在时域和频域。仿真结果表明，基于GA的FLC和PID控制器通过降低RMS头部加速度，头部的VDV，CF，AR_h和AR_ut来降低被动悬架系统，从而提供了更好的乘坐舒适性和健康状况。