摘要
电动助力转向系统是近年来迅速发展的一种新型动力转向装置,能够较好地解决汽车转向时轻便性和灵敏性的矛盾,并且具有节能、环保、容易装配等诸多优点。目前,电动助力转向系统正逐步取代液压助力和电液助力转向器,成为世界汽车技术发展的研究热点。
本课题来源于国家“863”计划项目,以某国产A0级轿车为对象,研究电动助力转向系统的稳定性和电流控制算法。本文就EPS系统的建模、稳定性、最优PID参数、电流控制策略和软硬件开发等方面进行了详细论述。全文共分为七章。
第一章是绪论。简要介绍了电动助力转向系统的工作原理、结构形式和分类。总结了电动助力转向系统在稳定性和电流控制算法方面的研究历史与发展现状,指出了本文研究的主要内容。
第二章是EPS系统的建模。本章采用MATLAB/Simulink建立了EPS系统模型,建模过程中采用PID反馈控制,通过分析地面反力的形成过程,将地面反力正比于齿条位移。建模过程中充分考虑了电机电气参数的变化、电流传感器的低通滤波性质和EPS控制器的滞后特性。最后采用频域和时域两种方法,通过电流扫频实验、阶跃实验和转向实验,对所建立的模型进行了验证。
第三章是EPS的稳定性分析。回顾了系统稳定性的基本概念和常用的判定方法,提出采用研究PID参数稳定域的方法来分析EPS系统的稳定性。通过绘制三维的PID参数稳定空间,得到了PID参数对系统稳定性的影响。在此基础上,通过分析系统参数的变化对PID参数稳定域的影响,研究了系统参数对EPS稳定性的影响。
第四章是基于遗传算法的最优PID参数研究。分析了EPS系统对稳定性、快速性和精确性的要求,指出了其中的矛盾。提出采用遗传算法对PID参数进行优化,以兼顾EPS的各项性能要求。在此基础上,分析了系统参数变化对最优性能指标和最优PID参数的影响,并分析了系统的鲁棒性,得到了各参数对系统性能的影响关系。
第五章是电流控制策略及其鲁棒性分析。通过分析系统参数对系统性能的影响,提出了以选择曲线型助力特性、电机转速前馈控制、蓄电池电压补偿和最优PID参数自适应方法为主要内容的电流控制策略。通过Monte-Carlo随机抽样试验,对控制系统的稳定性、电流跟随性和鲁棒性进行验证和评价。
第六章介绍了EPS软硬件系统的开发和实车实验。建立了电机试验台和EPS简易试验台,介绍了EPS控制器硬件的组成结构和各模块的实现方法,采用uC/OS-II嵌入式操作系统框架实现了EPS控制软件。测试了电机内阻和反电动势系数随电机电流的变化关系,采用电机参数自适应的方法获得了更精确的电机转速估计。最后,对EPS系统的稳定性和电流控制策略进行了实车验证。
第七章对全文进行了总结,并对将来的研究进行了展望。
通过对电动助力转向系统稳定性和电流控制的仿真分析和实车验证,主要得到以下结论:
(1)电机内阻、电机反电动势系数、助力增益和蓄电池电压对EPS系统稳定性影响较大。
(2)就对最优性能指标和最优PID参数的影响程度来说,电机内阻、电机反电动势系数、助力增益和蓄电池电压的影响较大,而电机电磁转矩系数、电机电感和地面反力弹性系数影响不大。
(3)采用曲线型助力特性、电机转速前馈控制、蓄电池电压补偿和最优PID参数自适应的方法可以提高EPS系统的电流跟随性能和鲁棒性。
(4)电机内阻和反电动势系数随电机电流的变化而变化,采用电机参数自适应的方法可以获得更精确的电机转速估计。
本文在以下3个方面有所创新:
(1)提出采用PID参数稳定域来研究EPS系统稳定性的方法,通过分析系统参数对PID参数稳定域的影响关系,得到这些参数对系统稳定性的影响。采用遗传算法对电流控制PID参数进行了最优整定,研究了系统参数对最优性能和最优控制参数的影响。
(2)提出以选择曲线型助力特性、电机转速前馈控制、蓄电池电压补偿和最优PID参数自适应方法为主要内容的电流控制策略,采用Monte-Carlo随机抽样试验的方法,对提出的控制策略进行了验证。
(3)提出基于电机参数自适应的电机转速估计方法。该方法中电机内阻和反电动势系数随电机电流的变化而变化,实验证明该方法具有更高的估计精度。
Electric power steering system is a new type power steering system developed rapidly in recent years. This new system can solve the contradiction between handiness and sensitivity, and has many advantages such as energy saving, environmental protection and easy assemblity. Recently, electric power steering system is gradually replacing the hydraulic and electro-hydraulic power steering system, and becoming automotive technology research focus all over the world.
The paper comes from the national 863 project, studying on the electric power steering system stability and current control algorithm to an A0 class car as an object, In this paper, EPS system modeling, stability, optimal PID parameters, current control strategies and hardware and software development are discussed in detail. Paper is divided into seven chapters.
Chapter I is an introduction. A brief introduction of electric power steering system principle, structure and classification was gived. The context of the history and development situation of electric power steering system stability and the current control algorithm were summed up. The main contents of this paper were pointed out.
Chapter II is EPS system model establishment. This chapter established the EPS system model with MATLAB/Simulink. In the modeling process, PID feedback control was used. By analyzing the formation of ground-reaction force, the ground reaction force was modled as proportional to the rack displacement. The changes to the motor electrical parameters, low pass filtering nature of current sensor and characteristics of EPS controller lag were taking into full account in modling process. Though the current sweep experiment, the current step experiment, and the steering wheel turning experiment of frequency domain and time domain methods, the model established was validated.
Chapter III is the analysis of EPS stability. The basic concepts of system stability and common determination methods were reviewed. To analyze the EPS system stability, the method of using PID parameters stability regions was proposed. The influence of system stability was studied by drawing three-dimensional PID parameters stability space. And then, the influence of the PID parameters stability region when system parameters are changing was studied, and then the influence on the system stability was got.
Chapter IV is the study on the optimal PID parameters with genetic algorithm. The stability, rapidity and accuracy of EPS system were analyzed. By taking into account of all the various performance requirements EPS, the method of using genetic algorithm to optimize PID parameters was proposed. On this basis, the influence of system parameters on the optimal performance and the optimal PID parameters along with the robustness of the system were studied, and the influence of parameters on the system performance were obtained.
Chapter V is the study of the current control strategy and its robustness. By analyzing the influence of system parameters on system performance, a current control strategy is proposed which content selecting the curvilinear assistance, motor speed feedforward control, battery voltage compensation and the optimal PID parameters adaptive method. By using Monte-Carlo random sampling test method, the EPS system stability, current control effect and robustness were evaluated.
Chapter VI describes the EPS software and hardware system development and the real vehicle validation. The development process of the motor testrig and EPS controller hardware were introduced by describing its composition and realization of each module. The EPS controller software was carried out using uC/OS-II embedded operating system. The motor back-EMF coefficient and the resistance which change with the electric current were measured, and then, a more accurate estimate of motor speed was achieved by varying motor parameters. And at last, the EPS system stability and the current control strategy were validated in a real vehicle.
Chapter VII gives a summary of the paper and a research prospect in the future.
Through simulation analysis and real vehicle validation for the electric power steering system stability and current control strategy, the main conclusions are as follows:
(1) EPS system stability is more sensitive for these parameters than the others: motor resistance, back-EMF coefficient, assist gain and battery voltage.
(2) The optimal performance and the optimal PID parameters are sensitive to motor resistance, back-EMF coefficient, assist gain a greater impact and the battery voltage, and insensitive to motor torque coefficient, motor inductance and the elasticity coefficient of the ground reaction force.
(3) Current control performance and robustness of EPS can be improved by using curvilinear assistance, motor speed feedforward control, battery voltage compensation and the optimal PID parameters adaptive method.
(4) Motor resistance and back-EMF coefficient change with the motor current, and a more accurate motor speed can be estimated using variable parameters.
This paper has been innovative in the following areas:
(1) The method of using PID parameters stability regions to analyze the EPS system stability was proposed. The influence on the system stability was got by studing the influence of the PID parameters stability region when system parameters are changing. The method of getting optimal PID parameters using genetic algorithm was proposed, and the optimal current control method and system robustness can be studied by analyzing the optimal performance and the optimal PID parameters.
(2) The current control strategy which contents curvilinear assistance, motor speed feedforward control, battery voltage compensation and the optimal PID parameters adaptive method was proposed. Monte-Carlo random sampling test method was proposed to verify the control strategy.
(3) A more accurate motor speed estimate method using variable parameters was proposed, in which motor resistance and back-EMF coefficient change with the motor current.
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