基于SIMPACK和MATLAB的ABS联合仿真

合集下载

基于 SIMPACK和 MATLAB的 ABS联合仿真

基于 SIMPACK和 MATLAB的 ABS联合仿真黄鼎友;张德华【期刊名称】《工业仪表与自动化装置》【年(卷),期】2013(000)003【摘要】不论是采用逻辑门控制算法还是采用PID控制算法，目前汽车制动防抱死系统ABS的研究往往都没有考虑到路面的不平度。

为了提高ABS的精度，降低开发成本，提高匹配效率，首先必须获得车辆各子系统的拓扑结构，再用多体动力学软件SIMPACK建立整车模型。

为了更加逼真的模拟实际道路情况，采用B级道路谱，在MATLAB中搭建4通道ABS的滑模控制器，进行了联合仿真。

该仿真模型，可以用于模拟分析不同工况、不同控制参数对制动性能的影响，可以方便快捷地验证不同控制策略的有效性。

结果显示：该方法可以逼真地模拟实际车辆制动过程，有效地缩短了制动时间和制动距离，提高了车辆的安全性，同时为ABS 的研发提供了一种新途径。

【总页数】5页(P20-23,29)【作者】黄鼎友;张德华【作者单位】江苏大学汽车与交通工程学院，江苏镇江212013;江苏大学汽车与交通工程学院，江苏镇江212013【正文语种】中文【中图分类】TP391.9;U461.6【相关文献】1.空气悬架SIMPACK与MATLAB联合仿真研究 [J], 李姣姣;陈龙;汪若尘2.基于SIMPACK和MATLAB的汽车半主动悬架模糊控制及联合仿真 [J], 刘勺华;贝绍轶;赵景波;陈龙3.基于ADAMS和MATLAB联合仿真的ABS试验分析 [J], 来翔;李守成4.基于ADAMS与MATLAB的汽车ABS控制策略的联合仿真 [J], 郑太雄;李倩敏;邬彪5.基于Matlab与ADAMS联合仿真的ABS系统分析 [J], 张辉;万芳;白锦洋;李陆浩;冯浩因版权原因，仅展示原文概要，查看原文内容请购买。

空气悬架SIMPACK与MATLAB联合仿真研究

空气悬架SIMPACK与MATLAB联合仿真研究李姣姣;陈龙;汪若尘【摘要】A multi-body dynamics model of an air suspension bus was built by using virtual prototype technique based on SIMPACK,and a neuron self-adaptive controller under MATLAB environment was designed. Then two road models -impulse input and random input were established by using the road builder in SIMPACK,and the co-simulation of SIMPACK and MATLAB were carried out,which results show that,comparing with the passive system, the air suspension system made up of the virtual prototype model and neuron self-adaptive control scheme can effectively reduce acceleration response in vertical vibration of the vehicle,restrain the variation in body atittude and improve the ride comfort.%利用虚拟样机技术建立了基于多体动力学软件SIMPACK的空气悬架客车模型,并基于神经元自适应控制理论在MATLAB中设计了神经元自适应控制器.通过SIMPACK中的路面编辑器建立了脉冲输入以及随机输入两种路面模型,进行了SIMPACK动力学模型与MATLAB控制策略的联合仿真研究.仿真结果表明,由车辆虚拟样机模型和神经元自适应控制策略组成的空气悬架系统,相比于被动悬架系统,有效降低了车身垂直振动加速度响应,抑制了车身姿态变化,改善了客车的行驶平顺性和乘坐舒适性.【期刊名称】《机械设计与制造》【年(卷),期】2012(000)001【总页数】3页(P185-187)【关键词】空气悬架;SIMPACK;神经元自适应;联合仿真【作者】李姣姣;陈龙;汪若尘【作者单位】江苏大学汽车与交通工程学院,镇江212013;江苏大学汽车与交通工程学院,镇江212013;江苏大学汽车与交通工程学院,镇江212013【正文语种】中文【中图分类】TH16;U463.331 前言随着人们对车辆平顺性要求的不断提高和悬架技术的发展，空气悬架因其自身的独有的特点，在车辆上的使用越来越广泛，因此，空气悬架成为当今汽车领域研究的一个热点。

基于MATLAB的汽车ABS制动过程仿真

Ｍｏｄｅｒｎ
现Ｍａ代ｎｕｆａ制ｃｔｕ造ｒｉｎｇ、＆工Ｐｒ艺ｏｃｅｓ装ｓＥ备ｑｕｉｐｍｅｎｔｌ ● ２ｏｌｓ￣￥４
基于ＭＡＴＬＡＢ的汽车ＡＢＳ制动过程仿真
宋龙龙，郑培，范满珍
ＭＡＴＬＡＢ，ｓｉｍｕｌａｔｉｏｎｏｆｔｈｅｃｈａｎｇｉｎｇｐｒｏｃｅｓｓｏｆｓｕｃｈｐａｒａｍｅｔｅｒｓａｓｃｅｎｔｅｒｏｆｗｈｅｅｌｓｌｉｐ，ｗｈｅｅｌｓｐｅｅｄ，ｌｉｎｅｓｐｅｅｄ，ｇｒｏｕｎｄ
滑移率、车轮中心速度、线速度、地面制动力和制动力矩等参数的变化过程仿真；第二，仿真出不同质心位置对防抱
制动系统的影响。由仿真图像可以清晰的看出每一个参数的变化过程，便于对今后ＡＢＳ的改进有更好的理论依
据，并且可知，当质心的位置由后向前变大时，可以使制动时间缩短，确保行车的安全。
—
ｂｒａｋｉｎｇｆｏｒｃｅａｎｄｂｒａｋｉｎｇｔｏｒｑｕｅａｒｅｃａｒｒｉｅｄｕｎｄｅｒｔｈｅｃｏｎｄｉｔｉｏｎｓｏｆｄｅｃｏｍｐｒｅｓｓ，ｐｒｅｓｓｕｒｅｂｏｏｓｔａｎｄｐｒｅｓｓｕｒｅｍａｉｎｔａｉｎｉｎｇ

基于Simulink的汽车ABS建模与仿真

基于Matlab/Simulink 的汽车ABS 建模与仿真摘要：本文阐述了ABS(防抱死制动系统)的基本结构、原理和控制特点。

在Simulink 的环境下以ABS(防抱死制动系统)滑移率为对象进行控制，根据ABS 系统原理建立了ABS 单车轮的仿真模型，并得出仿真曲线，验证汽车ABS 具有良好的制动性能和方向操纵性。

Modeling and Simulation of the Anti-Lock BrakingSystem based on MATLAB/SimulinkAbstract ：The article illustrates basic operations and control features of ABS system. Control the ABS Slip Ratio with Simulink, creates a single wheel ABS model according to the ABS principle. It produces Simulation curves ，which verifies that the Auto ABS has good braking performance and direction of the manipulation. 引言在遭遇紧急情况下，大多数驾驶员都会将制动踏板立即踩死。

在汽车制动时，如果车轮抱死滑移，车轮与路面间的侧向附着力将完全消失：如果只是前轮（转向轮）抱死滑移而后轮还在滚动，汽车将失去转向能力；如果只是后轮抱死滑移而前轮还在滚动，即使受到不大的侧向干扰力，汽车也将产生侧滑（甩尾）现象。

这些都极易造成严重的交通事故。

为了避免因车辆滑移而带来的交通事故，有必要研究一种以滑移率为对象进行控制的防抱死制动系统（ABS ）。

ABS 是提高汽车安全性能的主要因素之一，对于具有较高非线性的汽车制动过程，很难建立精确的数学模型；随着计算机技术和软件技术的迅猛发展，仿真技术已成为国内外研究的热点，并且在汽车研发中获得了广泛应用。

基于Simulink 防抱死制动系统 (ABS) 系统仿真

明显减少
THANKS
模型子系统、液压制动模型子系统、电机制动模型子系统。基于PID控制的ABS电动汽车单轮模型制动系统模
块的关系如图片所示
3
Simulink模型
2014
2015
2016
2017
车轮速度子系统
为了控制制动压力的变化率，该模型从期望的滑动量中减去实际滑动量，并将此信号馈入 bang-bang 控制（+1 或 -1，具体取决于误差的符号，请参见上图）。此开/关速率通过一阶时滞，该时滞表示与制动系统的液压管路相关联的延迟，为施加到车轮上的制动扭矩。
2
ABS防抱死系统原理
2 ABS的工作原理
ABS单轮模型
3
Simulink模型
3 simulink模型
添加项目
添加项目
单击编辑此项目的详细内容
添加项目
添项目ห้องสมุดไป่ตู้
添加项目
单击编辑此项目的详
单击编辑此项目的详
细➢内在容理论分析的基础上，利用simulink对汽车防抱制动系统的各个子系统进行图形仿真建模，主要细包内括容单轮车辆
基于simulink模型的车辆ABS系统
滑移率控制
CONTENTS
1 问题分析 2 ABS防抱死系统原理 3 simulink模型 4 仿真分析 5 结论
1
问题分析
1 问题分析
现状
在车辆紧急制动时，驾驶员踏板往往踩死，这种情况下，如果车轮抱死，车轮与路面间的侧向附着力将完全消失:如果只是前轮转向轮)先于后轮抱死，汽车将失去转向能力;如果只是后轮先于前轮抱死，汽车将产生侧滑( 甩尾)现象。ABS是提高汽车安全性能的主要因素之一，对于具有较高非线性的汽车制动过程，很难建立精确的数学模型。本文以轿车为研究对象，建立了ABS数学模型，采用 Simulink仿真软件对ABS进行仿真。单击编辑副标题

基于MATLAB的汽车ABS制动系统仿真研究

Internal Combustion Engine & Parts基于MATLAB的汽车ABS制动系统仿真研究周宁®;周辉于(①安徽三联学院机械工程学院，合肥230601;②洛阳理工学院，洛阳471023)摘要：汽车防抱死制动系统是现代汽车的关健部件，本文在基于Matlab软件中Simulink的基础上，以比亚迪F6的具体数据进行PID控制的A B S防抱死制动系统的建模，并针对高低不同附着系数的路面条件进行仿真性能的研究。

关键词院Matlab;防抱死系统;仿真研究0引言汽车防抱死制动系统是现代汽车普遍采用的一种主动安全装置，A B S装置的使用能够大大降低汽车在紧急制动时的事故率，提高驾乘人员的乘坐安全性。

汽车A B S系统一般由车轮速度传感器、制动压力调节装置、电子控制单元A B S EC：U等几部分组成，通过A B S E C U中的程序控制，能够有效地提高车辆在紧急制动时的安全性。

M atlab软件具有大量的工具包，功能强大。

Simulink 是实现动态系统建模和仿真的一个软件包，体现了 Matlab 软件的扩展与特色。

由于M atlab语言环境中Sim u link软件具有用户界面友好，操作方便等优点，所以它成为了目前工程界常用的仿真工具。

1基本原理目前，A B S系统在汽车上得到了广泛的使用，此系统是在普通制动系统的基础上增加了轮速传感器、压力调节器和电子控制单元E C U等装置，A B S系统的控制目标是将车轮滑移率控制在20%附近。

其工作原理主要依靠车速传感器收集的车速信号对车轮是否已经抱死进行判断，及基金项目：安徽三联学院校级一般自然科学科研项目《基于 M atlab的汽车A B S制动系统仿真研究》（编号：KJYB2017005 )。

作者简介：周宁（1988-)女，河北衡水人，硕士研究生，助教，现工作单位安徽三联学院机械工程学院，研究方向为车辆安全技术。

基于MATLAB的汽车ABS制动过程仿真

基于MATLAB的汽车ABS制动过程仿真ABS（Anti-lock Braking System，防抱死制动系统）是现代汽车上保证行车安全的重要制动系统之一。

ABS制动系统可以避免在制动时车轮抱死，从而提高了制动效果和稳定性。

为了深入理解ABS制动系统的工作原理和性能，本文将基于MATLAB软件进行汽车ABS制动过程的仿真。

一、建立模型和假设为了实现ABS制动过程的仿真，需要建立一个基于MATLAB 的系统模型。

该系统模型需要考虑以下几个方面：1. 汽车的运动方程。

2. 轮胎与地面的接触力，即摩擦力。

3. 制动器与车轮的接触力。

4. ABS控制器的控制策略。

在仿真过程中，假设车辆在制动前以一定的速度匀速行驶，制动时四个车轮的制动和抱死状态是相同的。

二、模型搭建在MATLAB界面中，首先利用simulink模块搭建模型。

模型如下：模型中包含了车辆运动方程、轮胎地面接触力、制动器与车轮接触力等模块。

其中，运动方程模块利用F=ma公式进行建模，轮胎地面接触力模块利用摩擦力系数进行计算，制动器与车轮接触力模块利用摩擦力系数和制动器力矩进行计算。

在模型中，还有制动器控制器模块，负责制动器的控制与调节。

制动器控制器可以采用PID算法或滑模控制算法来控制制动器的开闭和力矩大小。

三、仿真过程在进行仿真过程中，需要确定以下参数：1. 初始车速度v0=80km/h。

2. 初始刹车踏板角度θ=0。

3. 制动器摩擦力系数μs=0.7。

4. 刹车片初期转动半径r=0.05m。

在进行仿真操作前，应先在程序中设定好各参数，再设定仿真时间和仿真步长。

由于ABS制动过程会使用到控制器，因此应首先进行控制器的设计和仿真。

在此，控制器的设计采用滑模控制器，其仿真结果如下：控制器的仿真结果显示，在刹车操作开始10s后，滑模控制器调节出的制动器力矩逐渐增加并稳定于85N·m左右。

随着控制器的调节，车轮抱死现象得以解决、保持ABS制动状态下使车辆具备更好的稳定性和制动效果。

基于MATLAB／Simuli的汽车ABS半实… (

基于MATLAB/Simulink的汽车ABS半实物仿真摘要：本文所研究的是一种基于MATLAB/Simulink的汽车防抱死刹车系统（ABS）的半实物仿真的方法。

本方法利用Simulink提供的模型建立车辆的传动系模型、自动变速箱模型和ABS模型等。

所建成的这套半实物仿真系统既可在软件环境下对汽车进行仿真，也可以通过I/O接口与ABS系统相连接以观察系统的仿真效果，检验控制算法的合理性。

通过合理改变相应参数，本系统还可以模拟实际汽车在不同工况下的工作情况，极大提高了汽车电子设备的研发工作的效率。

同时，本系统也可用于教学演示。

关键词：Simulink，ABS,计算机仿真，半实物1 引言在汽车工业中，由于引进了大量的电子技术，使整车动力性、安全性、经济性、舒适性等性能得到大幅度提高。

为满足汽车电子设备研发的需要，我们建立了这套汽车电子半实物仿真系统。

本系统可以用来辅助汽车电子设备的设计、开发，减少实车实验的工作量，提高工作效率。

由于其良好的可操作性，也可作为教学演示软件使用。

2 半实物仿真由于计算机仿真是基于数学模型的仿真方法，虽然仿真成本较低，但仿真的效果取决于所建模型的质量。

在实际操作中，由于实物仿真系统很复杂，所以数学建模的难度较大。

有的系统甚至无法准确地建立数学模型。

而使用实物进行实验则受硬件设备及环境等因素的影响，成本过高，并且不容易模拟一些极限工况，所以应用也受到一定限制，而把实物系统放置在计算机仿真环节中进行仿真研究就可以解决上述问题，并能很好地综合以上两种方法的优点，所以，我们提出半实物仿真的思想。

在本文介绍的汽车半实物仿真系统中，既可以通过在计算机中建立数学模型进行仿真，也可以把仿真输出与实物汽车相连，以观察实际工作效果，验证所建数学模型的合理性和实物设备的效能。

从而降低成本，提高工作效率。

MATLAB以复数矩阵作为基本编程单元，集科学与工程计算、图形可视化、图形处理和多媒体等于一身，已在汽车工业等领域得到广泛的应用。

(仅供参考)simpack--matlab-联合仿真

SIMAT--The Link Between SIMPACK andMATLABSIMPACK Release8.816th March2006/SIMDOC v8.800COPYRIGHT INTEC GmbH2006cSIMAT:0.0-2Contents1Motivation 1.0-52Linear System Interface 2.1-72.1Linear System Matrices in MATLAB4.2...........2.1-7Motivation..........................2.1-7MATLAB-Format......................2.1-7MATRIX x-Format......................2.1-82.2Example Inverse Stick Pendulum..............2.2-93Co-Simulation Interface 3.1-133.1Co-Simulation........................3.1-13Motivation..........................3.1-13Principle Structure......................3.1-14How to Set Up the Co-Simulation Interface.........3.1-14SIMAT installation..................3.1-14Conﬁguration of the Co-Simulation.........3.1-17Conﬁguration of the SIMAT block..........3.1-18Conﬁguration of the SIMPACK Model.......3.1-21Autostart...........................3.1-22Start of the command server............3.1-23Simulation Output.....................3.1-24 4Limitations 4.0-255Platform and Version Support 5.0-27SIMAT:0.0-4CONTENTSSIMAT:1.MotivationA variety of tools highly optimized for a number of diﬀerent speciﬁcationsexists in theﬁeld of complex multidisciplinary simulation.Therefore it isoften advisable to use a multibody system(MBS)program together withanother application,e.g.a control design tool,to be able to take full ad-vantage of both programs’qualities,including“toolboxes“and“modules“developed for special purposes in special software environments.Furthermore,when diﬀerent teams are established for model developmentand for control design,each of them can work in its familiar software envi-ronment,on diﬀerent hardware platforms,share,interchange,and simulatemodels and results.This approach can also decrease software licence de-mands and hardware requirements.SIMPACK as an’open’MBS program oﬀers an interface to diﬀerent math-ematical analysis tools,among them MATLAB.The family of SIMAT-interfaces has been enlarged to meet diﬀerentrequirements.Figure SIMAT:1.0.1:SIMAT familyThe intention of these pages is to give a detailed explanation of how toinclude and simulate models deﬁned in the SIMPACK program package withthe help of MATLAB as well as hints how to choose the interface versionwhich is suited best to one’s needs.One part of the MATLAB program package is the graphical blockoriented tool SIMULINK.SIMULINK enables the user to combineSIMPACK models,both linear and non-linear,with other elements,con-tinuous or discrete,e.g.control elements,to form a complete systemrepresented in a block diagram form.The whole system can afterwards beedited,simulated and evaluated in the MATLAB program environment.Itis therefore possible to develop and evaluate control systems for the modelby the application of the latest control design approaches(including neuralnetworks,fuzzy control,etc.).MBS programs describe mechanical systems by sets of diﬀerential equa-tions.There are two major types of diﬀerential equations:ordinary diﬀer-ential equations(ODEs)and diﬀerential algebraic equations(DAEs).SinceSIMAT:1.0-6SIMAT:1.MOTIVATION the MATLAB-SIMULINK tool does not oﬀer a DAE solver,the SIMPACKmodel has to be either restricted to MBS systems described by ODE equa-tions,e.g.to systems without constraints,or a fundamentally new solutionhas to be introduced.Within SIMAT,the so-called Co-Simulation Inter-face has been ing this interface SIMULINK handles SIMPACKDAE models as discrete elements and calls the SIMAT block atﬁxed timesteps,while the DAE model itself is integrated by the SIMPACK kernelbetween theseﬁxed time points(see chapter5for more details).The SIMAT Interface allows the introduction of linear system matrices(Lin-ear System Interface)or non-linear models,by means of th Co-Simulation,to MATLAB.If a Code-Execution(codeex)license is available the exportedcode can be included to MATLAB.This can be done either as continuous so-lution(ODEs only),or if an additional solver license is available,as discretesolution where DAEs can be taken into acountSIMAT:2.Linear System InterfaceSIMAT:2.1Linear System Matrices in MATLAB4.2 MotivationSystems represented by linear system matrices generated by use of the Lin-ear System Interface are easily interchangeable not only between programpackages,but also between diﬀerent computer platforms.It is thus pos-sible to implement a model in SIMPACK,design a controller by the useof MATLAB tools and to work with the results in a MATLAB or a SIMPACKsimulation.SIMPACK oﬀers the possibility to generate a set of linear system matricesfor a multi-body system implemented by SIMPACK.These matrices can beused in other simulation and system analysis tools like MATLAB or MATRIX x.MATLAB is able to read either format,generated from SIMPACK,if theyhave theﬁle extension’∗.m’.MATLAB-FormatBy application of the corresponding option SIMPACK automatically gen-erates aﬁle in the MATLAB’∗.m−file’-format.The matrices have thefollowing form:A=[-.138730020788E+02.184742168926E+02.943934646297E+01-.310978870480E+03-.687226020569E+04-.566604517831E+05.471759253145E+04-.183519688420E+04-.100766856356E+04];B=[...];C=[...];D=[...];This model description can be loaded into MATLAB workspace just by exe-cuting model descriptionﬁleFILENAMESIMAT:2.1-8Linear System Matrices in MATLAB4.2The linear system matrixes are then available in the MATLAB workspace.MATRIX x-FormatSimilarly it is possible to generate linear system matrices in the MATRIX x’∗.ms’-format.In this case the matrices have the following form:A=[-.138730020782E+02,.184742168925E+02,.943934646297E+01;-.310978870482E+03,-.687226020569E+04,-.566604517331E+05;.471759253144E+04,-.183519688423E+04,-.100766856256E+04];B=[...];C=[...];D=[...];mv FILENAME.ms FILENAME.mExample:Inverse Stick Pendulum SIMAT:2.2-9SIMAT:2.2Example:Inverse Stick PendulumThe well known inverse stick pendulum will be the example ofapplication of the Linear System Interface.(see also$SIM-PACK/interfaces/simat/example)1.Create a working directory including:•theﬁle stick pen.sys•theﬁle stick pen.ani2.Start SIMPACK.Open the model stick pen and create the linearsystem matrices in the MATLAB m-ﬁle format(CALCULATIONS->Linear System Matrices->For SIMPACK+MATLAB).3.Simpack generates the MATLABﬁle stick pen.m in your current di-rectory.4.Start MATLAB.Load the linear system matrices to the workspace withthe command’stick pen’5.Now you can check the eigenvalues of the A-matrixeig(A)ans=2.9714-2.9714Since the matrix C is still null,now deﬁne C.Depending on the choice of C the system is either completely observ-able or not completely observable.It can be checked with the helpof MATLAB if the Control Toolbox is available:(a)C=[0,1,0,0](measurement of the pendulum angle)rank(obsv(A,C))(determine observability)ans=2system not observable with C=[0,1,0,0](b)C=[1,0,0,0](measurement of the wagon displacement)rank(obsv(A,C))(determine observability)ans=4system observable with C=[1,0,0,0]rank(ctrb(A,B))(determine controllability)ans=4system fully controllable6.Try to stabilize the system with the use of pole placement.Shift theclosed-loop poles to(-1,-1,-2.97,-2.97).The Control Toolboxoﬀers the routines place and acker.Toﬁnd the feedback coeﬃcientvector type:SIMAT:2.0-10Example:Inverse Stick PendulumFigure SIMAT:2.2.1:Inverse Stick PendulumK=acker(A,B,[-1,-1,-2.97,-2.97])(For function place no two poles can exactly have the same values,the diﬀerence between two poles may be very small,though.)MATLAB will answer:K=1.0e+03*0.0450 1.58640.12020.5573ing the SIMULINK State-Space block and these Parameters asfaktors for the states in a feedback loop a stable control loop can bebuild upExample:Inverse Stick Pendulum SIMAT:2.0-11Figure SIMAT:2.2.2:Inverse Stick PendulumSIMAT:2.0-12Example:Inverse Stick PendulumSIMAT:3.Co-Simulation InterfaceSIMAT:3.1Co-SimulationMotivationThe Linear System Interface described in the chapter SIMAT:2providesthe SIMULINK integrator with the state derivatives(the so-called right-hand-side)of the linearised SIMPACK model at a given integration step.This method is restricted to linearised models.However,also non-linear models should be integrated to MATLAB.As manymechanical systems contain constraints,their mathematical models havethe form of a DAE equation and therefore cannot be directly simulatedwithin SIMULINK,because there are no DAE solvers in the SIMULINK tool.Furthermore,the mechanical SIMPACK-model and that part of the modelset up in SIMULINK might require diﬀerent numerical algorithms,i.e.in-tegration methods.To overcome these problems,the Co-Simulation Interface was developed.Now,both simulated subsystems(in SIMULINK and in SIMPACK)can takeadvantage of highly optimized integrators for their speciﬁc tasks from theoriginal environments,also the maximal integration step-size can be usedfor both subsystems,independent from their mathematical description.SIMULINK enables the user to create and simulate so-called mixed typesystems.That means that both continuous and discrete blocks can be ar-bitrarily combined in one block diagram.Therefore the Co-Simulation In-terface can be embedded into an ordinary discrete block on the SIMULINKside,pretending discrete behaviour of the interface block to SIMULINK,while the whole SIMPACK model is simulated inside SIMPACK as a conti-nous model between the discrete time points(seeﬁg.SIMAT:3.1.1).Figure SIMAT:3.1.1:Co-simulation integration procedureSIMAT:3.1-14Co-SimulationPrinciple StructureThe SIMAT Co-Simulation Interface is a two-prozess solution.Bothprozesses SIMPACK and MATLAB are solving their part of the equationsystem independently between discrete time points.The discrete timepoints are determined by the sample time period which has to be givenas a parameter by the user.If one sample time period is elapsed bothsolvers are forced to stop and the interconnecting vectors[U]and[Y]areexchanged.After that the simulation continues untill the next time stepis reached.All time steps are equidistant.The SIMAT Co-Simulation isa Master-Slave conﬁguration.The integration parameters like start time,end time,sample time are given by the Master(MATLAB)on which theSlave(SIMPACK)reacts.System speciﬁc results can be postprocessed ineither system,this means results are available in the SIMPACK General2D plot and3D Animation.The data exchange is carried out by a socketbased TCP/IP communication.With that both systems don’t have to beavailable on one computer but within a computer network,where the com-puters with either software can be identiﬁed by their IP-address.Even aCo-Simulation via the Internet is possible.The comunication is carried outby a Client-Server conﬁguration.The Server(SIMPACK)creates a socketon it’s local PC to which the Client(MATLAB)connects.The socketcan be identiﬁed by it’s port number and the local PC’s IP-Address.Theconection between MATLAB and the CO-Simulation socket is realised byan SIMULINK S-Function which can be parametrised by the apropriateSIMAT block To start a SIMAT Co-Simulation SIMPACK has always to bestartedﬁrst.Any modiﬁcations within the SIMAT-block require a runningserver as MATLAB carries out an initialisation call of the S-Function assoon as a block modiﬁcation is conﬁrmed.How to Set Up the Co-Simulation InterfaceSIMAT installationTo use the Co-Simulation the path where the SIMAT-block and the apro-priate S-Function are positioned have to be made available for MATLAB.Theﬁles are located in:$SIMPACK/run/interfaces/simat/¡MATLAB Release¿/$SIMPACK CPUTYPand can be accessed via the MATLAB GUICo-Simulation SIMAT:3.1-15Figure SIMAT:3.1.2:set MATLAB path to SIMATﬁlesSIMAT:3.1-16Co-SimulationThe path setting has only to be done once a new SIMPACK version isinstalled.If the path was set correctly SIMAT is available by typing”simat”to the MATLAB shell.The SIMAT block can be treated like and SIMULINKS-Function blockFigure SIMAT:3.1.3:SIMAT co-simulation window(I)Co-Simulation SIMAT:3.1-17 Conﬁguration of the Co-SimulationFigure SIMAT:3.1.4:Co-Simulation Conﬁguration WindowThe communication and consistency settings are:•Serial/Parallel Communication Set the Communication Mode for theCo-Simulation.–With enabled serial Communication Mode(is also the defaultMode)the Co-Simulation Master integrates within the currenttime-intervalﬁrst and transfers the results after the integrationto the Co-Simulation Slave.Now the Slave integrates to theend of the current time-interval and transfers the results to theMaster.–With enabled parallel Communication Mode both Co-Simulation Partner integrates parallel to the end of the cur-rent time-interval and transfers then there both results to theCo-Simulation Partner.SIMAT:3.1-18Co-Simulation–This setting is also available via command line option--comm=serial or--comm=parallel.Note,the commandline setting will overwrite the num6-ﬁle settings.•Enable/Disable Consistency Set the Consistency Flag for the Co-Simulation.–With enabled Consistency(is also the defaultﬂag),both Co-Simulation Partner creating a consistent start vector U0be-fore the Co-Simulation Init-Call.Note:Start vector for theConsistency-Call is the U0vector deﬁned in the sys-ﬁle–With disabled Consistency,both Co-Simulation Partner startingthe Co-Simulation with the U0vecter deﬁned in the sys-ﬁle.–This setting is also available via command line option--cons=enabled or--cons=disabled.Note,the The com-mand line setting will overwrite the num6-ﬁle settings.From the command line:>simpack--help...****cosim_server[OPTION]TASK-FLAG MODEL-NAME**cosim_client[OPTION]TASK-FLAG MODEL-NAME**----------**master(default)**slave**matlab**amesim****OPTION:--port[=PORT-NUMBER](default20000)**-------**--address[=IPv4-ADDRESS](default127.0.0.1)****--comm[=COMMUNICATION-FLAG]**serial(default)**parallel****--cons[=CONSISTENCY-FLAG]**enabled(default)**disabled****--load-model[=LOAD-MODEL-FLAG]**active(default)**passive**...Conﬁguration of the SIMAT blockThe Co-Simulation can be carried out with several options:1.both systems(SIMPACK and MATLAB)accessible to one or diﬀerentcomputers2.SIMPACK Co Simulation will be started manually by the user orautomatically by MATLABCo-Simulation SIMAT:3.1-19 In any case the”Sampling Period”and the”TCP-Port”of server processhave to be given.Figure SIMAT:3.1.5:SIMAT parameter block1.The TCP-Port has to be equal to the cosim.slave.port given in theSIMPACK¡model¿.num6ﬁle if no”Auto start”option is selected.If the”Auto start”Option is selected the TCP-Port must be equalto the port number given with the Command Server execution(seebelow)2.in case SIMPACK is installed on a diﬀerent machine theRemote Server button has to be selected and the internet addressof the remote server process has to be edited in the line belowFigure SIMAT:3.1.6:SIMAT Remote Server3.The Auto start button has to be selected if the SIMPACK Co-Simulation should be started by MATLAB.The path and the nameof the SIMPACK model have to be edited in the line belowSIMAT:3.1-20Co-SimulationFigure SIMAT:3.1.7:Enable auto startFigure SIMAT:3.1.8:U-Vector UpdateCo-Simulation SIMAT:3.1-21Conﬁguration of the SIMPACK ModelTo carry out the SIMAT Co-Simulation the SIMPACk Model needs to haveat least one input(u-vector)and one output(y-vector).Both can bedeﬁned via the according icons in the SIMPACK gui1.In the given example theﬁrst external input(u-vector)to SIMPACKis allocated to theﬁrst internal time signal.Like in Time Excitationsthe internal time signals can be used as time depending externalforces or in rheonomic joints.Figure SIMAT:3.1.9:deﬁnition of the u-vectorSIMAT:3.1-22Co-Simulation2.The y-output vector can contain any values available in SIMPACK likeJonit states,Forces,Constrained Forces etc.and are to be deﬁndevia the apropriate icon.Figure SIMAT:3.1.10:deﬁnition of the y-vector3.If the Co-Simulation is started manualy the port on which thesocket will be installed has to be edited in the¡model¿.num6ﬁleby:cosim.slave.port=¡port¿If the conﬁguration of the SIMPACK model is complete the Co-Simulationcan be started:AutostartIf the user enables the auto start mechanism within the SIMAT parameter-block GUI,then the SIMPACK model name must be given.Note that thismodel must contains the full path including the sys-extention.To usethis functionality,it is necessary to have a waiting command serveravailably(see SIMAT:3.1).If the command server runs on a remotemachine it is necessary to specify the internet address(IPv4-address)ofthe remote host.If all parameters with the parameter-block GUI are set,press apply to connect to the command server.Now it is possible to start,stop or hold up the simulation within the Simulink GUI.NOTE:After astop-simulation,it is possible to start the simulation again,withoutany action on the SIMPACK GUI!Co-Simulation SIMAT:3.1-23Figure SIMAT:3.1.11:start SIMAT Co-SimulationFigure SIMAT:3.1.12:Enable auto startStart of the command serverIf the command server is not started yet,then check out the followingsteps:•start a SIMPACK command shell,because the command-server needsthe SIMPACK environment.•start the command server via>$SIMPACK/run/bin/bin_$SIMPACK_CPUTYP/cmd_server$EXEEXT20000listening on port20000.•if the port is available,the command server is ready and waiting forclients to connect...************************************************************************This is the SIMPACK command-server with TCP/IP socket interface.**SIMPACK Release8800.SIMAT:3.1-24Co-SimulationFigure SIMAT:3.1.13:Enable remote server**Copyright INTEC GmbH,D-82234Wessling,Germany.**********************************************************************[cmd]Creating socket at port20000.[cmd]Command server ready and waiting for client to connect.>•if you start the command server on a remote machine,notice theinternet address(IPv4)for the SIMAT-Block.Simulation OutputTo use the SIMPACK post-processing after simulation the SIMPACK MBSmodel states as well as the SIMULINK inputs to the SIMPACK model canbe saved into separateﬁles during simulation run time.The outputﬁlesare located in the output directory.The name of the targetﬁle for the states is<model>.izu.If the sampling period is non-zero,the Co-Simulation Interface will writethe SIMULINK integration results into thisﬁle for every sampling period ofthe SIMPACK block.Additionally,information about the input vector to the SIMPACK MBSmodel is saved in theﬁle<model>.uex.The twoﬁles will be used by the SIMPACK postprocessing modules.Re-sults and movements can be plotted and animated within SIMPACK.Thisrequires processing of the data with the execution of the SIMPACK module’calculate measurements’from the SIMPACK menu.SIMAT:4.LimitationsMBS programs describe mechanical systems by sets of diﬀerential equa-tions.There are two major types of diﬀerential equations:ordinary dif-ferential equations(ODEs)and diﬀerential algebraic equations(DAEs).Amulti body system without closed loops(and therefore without constraints)can in most cases be represented in the explicit form of an ODE.On theother hand,systems with closed loops(and thus with constraints)are repre-sented in the form of DAEs.Unfortunately the present SIMULINK version,1.3c,oﬀers ODE solvers only.For that reason,the SIMAT Function CallInterface(chapter4)is restricted to systems which can be solved by anODE solver,in other words,systems without kinematically closed loops.However,SIMPACK systems in DAE formulation can be simulated withinSIMULINK with the help of the Co-Simulation interface,which transformsa SIMPACK DAE model to a SIMULINK discrete block during simulation.While there can be an unlimited number of SIMPACK models via the LinearSystem Interface and the Symbolic Code Interface,only one model usingthe Function Call Interface or the Co-Simulation Interface can be used ina SIMULINK model at the same time.SIMAT:4.0-26SIMAT:4.LIMITATIONSSIMAT:5.Platform and Version SupportSIMAT is available for Windows and for RedHat Linux(Redhat8-RedHatES4)on32bit platforms.。

基于SIMPACK和MATLAB的汽车半主动悬架模糊控制及联合仿真

ｓｓｅｂｓｄｏＭＰＡＣＫａｄＭＡＴＬｙｔｍａｅ－ｎＳＩｎＡＢ
ＬＵｈｏｈａ，ＥＩｈｏｙ２ＺＩＳａ－ｕＩＢａ－ｉ，ＨＡＯＪｎ－ｏ，ＨＥＮＬｎＳｉｇｂ２Ｃｏｇ
（ｃｏｌｆｕｏｏｉｎｉｅｒｇＣａｇｈｕＩｓｔｔｏｃａｏｉＴｃｎｌｇ，ｈｎｚｏ４ＣｉａｈｏｏｔｍｂｌＥｇｎｅｉ，ｈｎｚｏｔｕｅｆＳＡｅｎｎｉＭｅｈｔｎｃｅｈｏｙＣａｇｈｕ２１，ｈｎ）ｒｏ１３６
２基于ＳＭＡＫ整车动力学模型ＩＰＣ
２１前悬架模型．
吕河教型轿车前悬架采用麦弗逊式独立悬架。ＳＭＰＣ在１ＡＫ
★ 来稿口：１— ２１－基金项目：期２１０ — ０ｋ０江苏省科技支撑项日（Ｅ０８１）Ｂ２０１４ｌ前悬架模拓扑锂
ｗｅｅｒｄｃｄｂ０６，８０％。０４％．２１％ｒｓｅｔｅｙｃｍｐｒｄｗｉａｓｖｕｐｎｉｎｓｓｅｒｅｕｅｙ１．％１．３７２．８１．３ｅｐｃｉｌｏａｅｔｐｓｉｅｓｓｅｓｏｙｔｍｖｈ
应用于控制系统分析与设计的１具箱，二对控制系统仿真技术的发
展和应用起到巨大的推动作用ＩＪ。应用ＳＭＰＣＩＡＫ和ＭＡＬＢ软ＴＡ
件对装有半主动悬架的昌河某微型轿车进行整车动力学联合仿真分析。采用多体动力学软件ＳＭＰＣ／ＡＫ建立整车动力学模型，利用ＭＡＬＢＳｍｌｋＴＡ／ｕｉ设计模糊控制器，通过建立车辆联合仿ｉｎ真系统来进行控制，研究车辆半主动悬架系统行驶平顺性。

基于Simulink的汽车ABS建模与仿真

基于Simulink 的汽车ABS 建模与仿真汽车防抱死制动系统(ABS)是一种很关键的汽车主动安全技术。

本文采用基于有限状态机的系统仿真方法，采用Simulink 建模，对ABS 模型中的连续系统和离散系统进行仿真。

仿真结果表明，该仿真系统能比较真实地反映汽车ABS 系统的实际工作过程，显著缩短制动距离，提高安全性。

通过对ABS 建立理论模型并进行计算机仿真，可以初步确定ABS 的一些参数，还可以通过仿真结果来验证和分析控制逻辑。

因此，对ABS 的仿真分析可以有效缩短开发周期，减少开发成本，并通过少量的试验验证，可作为实际ABS 性能分析及控制逻辑的模型。

1、ABS 仿真模型建立的理论依据汽车制动时的附着系数与滑移率的关系曲线如图1所示，为获得最佳的制动效能，应将车轮滑移率控制在10%-30% 的范围内，当滑移率为2O%时，其纵向附着系数达到峰值，制动效果最好。

因此，通常把2O%的滑移率称为理想滑移率或最佳滑移率。

本设计的仿真系统取滑移率控制范围为18%--22%。

本文仿真系统的建立基于单车轮模型，单车轮的受力制动过程模型如图2所示，b x t d J T F R d ω=- (1)x dv M F dt = (2)通常车轮制动扭矩与轮缸压力成正比，即：b T K P =⨯ (3)t x d J K P d F R ω-⨯+⨯= (4)因此可得车轮滑移率： V V V ωλ-=(5)式中M--车轮承受的质量；V--车身速度；V ω--车轮速度；x F —地面制动力；J —车轮转动惯量；ω--车轮角速度；R--车轮滚动半径；b T --制动器扭矩；K--制动力矩系数；P--轮缸压力； λ—滑移率。

本仿真系统采用的汽车模型参数如表1所示：表一汽车模型参数2、ABS仿真模型的建立及参数设置ABS系统仿真模型如图3所示:图3 ABS系统仿真模型3、ABS系统仿真结果对初速度为25Km/h的汽车ABS系统进行计算机仿真，仿真结果如图4和图5所示。

空气悬架SIMPACK与MATLAB联合仿真研究

【摘要】利用虚拟样机技术建立了基于多体动力学软件ＳＭＡＫ的空气悬架客车模型，并基于神ＩＰＣ经元自适应控制理论在ＭＡＬＴＡＢ中设计了神经元自适应控制器。通过ＳＭＰＣＩＡＫ中的路面编辑器建立了脉冲输入以及随机输入两种路面模型。进行了ＳＭＰＣＩＡＫ动力学模型与ＭＡＬＢ控制策略的联合仿真研究。ＴＡ仿真结果表明，由车辆虚拟样机模型和神经元自适应控制策略组成的空气悬架系统，相比于被动悬架系统，有效降低了车身垂直振动加速度响应，抑制了车身姿态变化，改善了客车的行驶平顺性和乘坐舒适｝。生关键词：空气悬架；ＩＡＣ神经元自适应；ＳＭＰＫ；联合仿真【ｂｔｃ】ｕｉｂｄｎｍｃｍｄｌｉｓｓｅｓｎｂｓＡｓａｔＡｍｌ－ｏｙｙａｉｏｅｏａａｐｎｉｕｒｔｄｓｎｒｕｆｏｂｉｉｒａｐｏ — ｕｔｙｕｎｖｔｌｒｏｌｂｓｇｉｕｔ
十一十ｄ一ｔ ’ 十、 ●一十ｄ ’ｄｌ十Ｊ十ｄ ’ 十ｄ十ｑ、ｑ、 ● ｔ、ｅｑ、ｔ、 § 、ｔ、ｔ１、§一十十’ ／千ｔ／巾’ ｑ、 ●一／、ｔ、ｅ、ｔ、ｔ、ｔｑ、 ● １ｔｔｅＣ－ｉｕ￣ｉｎｏＩＡＣｎＡＬＢｗｒｃｒｉｕ，ｈｃｅｕｓｕｌｒｉＩＡＫ，ｎｈＯｓｍｌｏｆＳＭＰＫａｄＭＴＡｅｅａｒｄｏｔｗｉｒｓｈｄｅｈｓｏａ，ｏｐｒｇｗｔｅｐｓｅｓｓｍｔｅａｕｐｎｉｙｔｍｍａｅｕｅｖｒａｐｏｏｅｈｗｔｔｃｍａｉｉｔａｉｙｔ，ｈｉｓｓｅｓｎｓｓｄｐｏｔｉｕｒｔｙｈｎｈｈｓｖｅｒｏｅｆｈｔｌｔｐｍｄｌｄｎｕｏｅ－ｄｐｉｅｃｎｒｌｃｅｅＣｅｔｅｄｃｃｅｅａｉｓｏｓｅｔａｖ— ｏｅａｅｒｎｓＩａａｔｏｔｈｍａｅｃｉｌｒｕｅａｃｌｔｎｒｐｎｅｉｖｒｃｉｎｆｖｏｓｎｆｖｙｅｒｏｅｎｉｌ－ｂａｉｎｏｅｖｈｃｅｒｓａｅａｉｉｎｉｏａｉｕｅａｄｉｐｏｅｔｅｒｅｏｆｒｒｏｔｅｉｌ，ｔｉｔｒａｏｂｔｔｄｎｒｖｉｍｏｔｔｆｈｅｒｎｈｖｔｎｔｍｈｄｃ．

基于MATLAB_Simulink的ABS仿真

基于MATLAB/Simulink的ABS仿真研究摘要：为了研究ABS的制动过程，本文在分析汽车制动防抱死系统(ABS)工作原理的基础上，在MATLAB/Simulink环境下构建ABS动力学模型进行仿真实验，研究ABS对整车性能的影响，并绘制相关参数仿真曲线进行分析研究。

结果表明，ABS装置对车辆制动性能有较大影响。

关键词：仿真；ABS；MATLAB/Simulink；车辆动力学模型Simulation Study of the Anti-Lock Braking Systembased on MATLAB/SimulinkAbstract: In order to study the ABS braking process, this paper analyzed the working principle of ABS, built ABS vehicle dynamic model with MATLAB/Simulink methods to make simulation experiment, researched the influence of vehicle performance caused by ABS and researched the relevant parameters stimulation curve. The result shows that the ABS has a great impact on vehicle braking performance. Key words: stimulation；ABS；MATLAB/Simulink；vehicle dynamic model0.引言ABS(Anti-lock Braking System)，即车辆防抱死制动系统，是一种主动安全装置，它能够缩短汽车制动距离，增加汽车制动时的方向稳定性，减少汽车制动过程中的侧滑现象，提高汽车制动时的安全性能，减少交通事故的发生，已成为当今车辆的必备装置。

simpack matlab 联合仿真

MATLAB - Format . . . . . . . . . . . . . . . . . . . . . . 2.1 -7
MATRIXx - Format . . . . . . . . . . . . . . . . . . . . . . 2.1 -8 2.2 Example Inverse Stick Pendulum . . . . . . . . . . . . . . 2.2 -9
1.0 -5
2 Linear System Interface
2.1 -7
2.1 Linear System Matrices in MATLAB 4.2 . . . . . . . . . . . 2.1 -7
Motivation . . . . . . . . . . . . . . . . . . . . . . . . mulation . . . . . . . . . 3.1 -17
Conﬁguration of the SIMAT block . . . . . . . . . . 3.1 -18
Conﬁguration of the SIMPACK Model . . . . . . . 3.1 -21
4 Limitations
4.0 -25
5 Platform and Version Support
5.0 -27
SIMAT: 0.0 -4
CONTENTS
SIMAT: 1. Motivation
A variety of tools highly optimized for a number of diﬀerent speciﬁcations exists in the ﬁeld of complex multidisciplinary simulation. Therefore it is often advisable to use a multibody system (MBS) program together with another application, e.g. a control design tool, to be able to take full advantage of both programs’ qualities, including “toolboxes“ and “modules“ developed for special purposes in special software environments. Furthermore, when diﬀerent teams are established for model development and for control design, each of them can work in its familiar software environment, on diﬀerent hardware platforms, share, interchange, and simulate models and results. This approach can also decrease software licence demands and hardware requirements. SIMPACK as an ’open’ MBS program oﬀers an interface to diﬀerent mathematical analysis tools, among them MATLAB. The family of SIMAT - interfaces has been enlarged to meet diﬀerent requirements.

基于MatlabSimulink的整车ABS控制算法仿真研究

基于Matlab/Simulink的整车ABS控制算法仿真研究作者：李涛陈光耀张志猛来源：《粘接》2020年第06期摘要：汽车防抱死系统是保障汽车安全行驶的重要部件，如何做好该部件的设计工作一直以来都是相关单位十分重要的研究课题之一。

因此，本次研究基于Matlab与Simulink对整车防抱死系统进行了仿真分析，并提出相关的控制算法，旨在优化防抱死系统的动力学性能，为该部件的优化设计提供理论基础。

关键词：防抱死系统;Matlab;Simulink;控制算法;仿真分析中图分类号：U461.91：TP391.9文献标识码：A文章编号：1001-5922（2020）06-0082-04ABS系统的全称为antilock brake system，翻译成中文为“制动防抱死系统”，本次简称为防抱死系统。

汽车在行驶过程中往往需要进行大量不同程度的刹车操作，而在汽车行驶速度过快或路面光滑的情况下，由刹车操作所造成的车闸抱死将会严重威胁国内人员和路人的生命健康安全[1]。

在没有发生交通安全事故的情况下，防抱死系统的不合理设计也会影响到相关部件与轮胎的使用寿命[2]。

因此需要通过针对防抱死系统的合理化设计来提高整车运行的安全性和稳定性。

1 汽车车辆模型建模1.1 车辆整车模型汽车模型属于典型的四轮车辆模型，该模型的设计涉及车辆运动的四车轮转动、车轮转角、横摆运动与纵向运动，建立车辆整车模型的目的在于模型车辆操纵、制动等状况下的力学特征[3]。

图1为四轮车辆模型结构。

在该模型中，将整车质量看作为簧上、簧下质量之和，不考虑风阻、轮胎滚动阻力以及车辆侧倾的影响，只考虑横向、纵向以及绕车辆惯性轴的转动，可建立如下模型：1.2 车辆车轮运动模型车轮转动方程由驱动力矩方程、地面与车轮间的摩擦力矩方程、制动器制动力矩方程所组成，本次研究针对后两轮驱动型车进行分析，所得到的方向如下所示：1.3 车轮轮胎模型轮胎所受的力是车辆行驶的动力，所涉及的力包括翻转力矩、回正力矩、侧倾力、侧偏力、纵向制动力以及驱动力等。

基于Simscape的车辆ABS建模与仿真研究

Ｉｎｏｒｄｅｒｔｏｔａｃｋｌｅｔｈｅｓｅｐｒｏｂｌｅｍｓ，ｔｈｉｓａｒｔｉｃｌｅｐｒｏｐｏｓｅｄａｐｈｙｓｉｃａｌｓｙｓｔｅｍｍｏｄｅｌｉｎｇｍｅｔｈｏｄｂａｓｅｄｏｎｓｉｍｕｌａｔｉｏｎｔｏｏｌ
ｍｏｄｅｌｂｕｉｌｔｂｙｔｈｉｓｎｅｗｍｅｈｏｔｄｈｓａｇｒｅａｔｉｎｄｅｐｅｎｄｅｎｃｅａｎｄｕｎｉｖｅｓａｒｌｉｔｙ．Ｏｎｔｈａｔｂａｓｉｓ，ｔｈｅｂｒａｋｅｐｒｏｃｅｓｓｗａｓｓｔｕｄｉｅｄ
ＡＢＳＴＲＡＣＴ：ＦｏｒｍｏｄｅｌｉｎｇａｎｄｓｉｍｕｌａｔｉｏｎｏｆｖｅｈｉｃｌｅＡＢＳｓｙｓｔｅｍ，ｔｈｅｒｅｉｓｔｈｅｌａｃｋｏｆｓｐｅｃｉｉｆｃｃｏｍｐｏｎｅｎｔｓｏｆｔｈｅｖｅ — ｈｉｃｌｅｍｏｄｅｌａｎｄｔｈｅｃｏｍｐｌｅｔｅｐｈｙｓｉｃｌａｓｙｓｔｅｍｍｏｄｅｌ，ａｎｄｐｕｒｅｍａｔｈｅｍａｔｉｃｓｔｈｅｏｒｙｍｏｄｅｌｉｓｏｂｓｃｕｒｅａｎｄｉｄｅｌｉａｚａｔｉｏｎ．
程的混合建模和仿真，比传统模型更具物理性和更切合实际情况，且构建的车辆组件模型具有独立性和通用性。为验证物

基于Carsim Simulink的ABS系统建模与仿真.

Page 16
Thank you！
Page 17
Page 5
ABS的控制目标
ABS的控制目标：滑移率S
Page 6
ABS的控制过程
Page 7
ABS控制算法
1.逻辑门限值控制 2.PID 控制 3.最优控制 4.滑模变结构控制 5.模糊控制 6.神经网络
Page 8
逻辑门限值控制
其基本的原理是利用车轮加减角速度门限及参考滑移率构成，防抱死逻辑使滑移率在车轮峰值附着系数附近波动，从而获得较大的车轮纵向和横向力；优点：不需要建立具体系统的数学模型，控制过程比较简单，结构原理上比较容易实现，并且对系统的非线性控制很有效；缺点：需要进行大量的道路试验，开发时间相对较长，成本较高；逻辑门限值是开发ABS首选的控制方法。
Page 9
PID控制
PID控制是一种基于经典理论的控制方法，最大优点是不需要了解被控对象的数学模型，只需要根据经验进行调节器参数调节，这个特点正好满足了ABS系统建模比较困难的特点；
缺点：实际操作中很难确定一种准确的轮胎模型来实时确定不同制动工况下的期望滑移率。
Page 10
PID控制框图
制系统。
功能： 1、提高制动时的方向稳定性
2、缩短制动距离
Page 3
ห้องสมุดไป่ตู้
ABS的发展历史
ABS技术最早由英国人霍纳摩尔于1920年研制发明并申请专利；
1930年代ABS在铁路机车的制动系统中得到运用；
1940年代末，飞机制动系统开始采用ABS，很快ABS成为飞机的标准配置；
Page 4
ABS的发展历史
2018/11/20
基于 Carsim/Simulink的 ABS系统建模与仿真