GA-based multi-objective optimization of active nonlinear quarter car suspension system—PID and fuzzy logic control

IF 3.4 Q2 MATERIALS SCIENCE, MULTIDISCIPLINARY International Journal of Mechanical and Materials Engineering Pub Date : 2018-11-22 DOI:10.1186/s40712-018-0096-8
Mahesh P. Nagarkar, Yogesh J. Bhalerao, Gahininath J. Vikhe Patil, Rahul N. Zaware Patil
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引用次数: 21

Abstract

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.

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基于遗传算法的主动非线性四分之一汽车悬架系统多目标优化——pid和模糊逻辑控制
悬架系统的主要功能是将车身与道路不规则性隔离开来,从而提供乘坐舒适性,并支持车辆并提供稳定性。悬挂系统必须执行冲突要求;因此,被动悬架系统被主动悬架系统所取代,主动悬架系统可以向系统提供力。主动悬架为车身与车轮的动态响应提供能量,实现车身与车轮的相对运动,从而提高悬架系统的性能。研究了非线性四分之一汽车悬架系统的建模和控制优化问题。建立了非线性四分之一小车的数学模型,并在Matlab/Simulink?环境。选择C类道路作为输入路况,车辆行驶速度为80kmph。采用FLC和PID控制动作实现悬架系统的主动控制。采用基于遗传算法(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,而不是猜测和试错方法。将优化函数建模为包含频率加权RMS座椅加速度、振动剂量值(VDV)、RMS悬架空间和RMS轮胎挠度的多目标问题。采用ISO 2631-1标准评估乘坐和健康标准。在Matlab/Simulink环境下对非线性四分之一模型和控制器进行了建模、仿真和优化。结果表明,与PID和被动悬架系统相比,ga优化后的FLC具有更好的控制效果。进一步的仿真验证了该悬架系统的座椅和人体模型。观察的参数包括频率加权的头部加速度均方根值、头部的VDV、波峰系数以及头部和上身的振幅比。(AR_h和AR_ut)。给出了时域和频域的仿真结果。仿真结果表明,基于ga的FLC和PID控制器通过降低被动悬架系统的RMS头部加速度、头部VDV、CF以及AR_h和AR_ut,获得了更好的平顺性和健康指标。
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来源期刊
CiteScore
8.60
自引率
0.00%
发文量
1
审稿时长
13 weeks
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