布式驱动电动汽车直接横摆力矩控制研究
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摘要
在如今环境污染和能源危机的背景下，电动汽车进入了高速发展的时期。分布式驱动电动汽车（IEV）是一种全新形式的电动汽车，它通过置于车轮轮辋内的轮毂电机驱动车轮，给整车提供动力。由于IEV车辆结构和动力学特性发生很大变化，因此IEV车辆的稳定性也是需要研究的新问题。
DYC系统是针对车辆稳定性提出的完备的车辆主动安全控制系统，研究和开发针对IEV车辆稳定性的DYC系统具有两方面的重要意义。一方面，DYC系统可以解决IEV车辆的稳定性问题，包括对IEV车辆重要状态观测和对IEV车辆稳定性控制。另一方面，IEV车辆结构给DYC系统提供了一个更好的平台，DYC系统可以在IEV车辆上实现在传统结构车辆上很难实现的驱动DYC控制或综合DYC控制形式，发挥更好的控制效能，IEV车辆也因此可以获得更高的稳定性。
然而，现有IEV车辆DYC系统研究存在一些不足，如对轮胎状态估计不足，不能充分把握控制边界；直接基于车辆侧偏角控制的研究较少，不能直接控制车辆稳定性；使用方向盘转角估计驾驶员意图，有时可能会导致控制失去意义；前后轮纵向力固定分配，影响控制效果。
针对上述问题，本文依托国家重点基础研究发展计划（973计划）“高性能分布式驱动电动汽车关键基础问题研究（2011CB711201）”，采用基于模型的设计方法（MBD）研究和开发IEV车辆DYC系统。
本文具体研究工作如下：
根据MBD开发流程，本文首先建立了IEV车辆模型，为DYC系统开发提供仿真平台。本文在IEV车辆模型中集成了郭孔辉教授提出的UniTire轮胎模型和最优预瞄侧向加速度驾驶员模型，用以提升模型精度、实现人—车闭环试验仿真。
其次，本文建立了车辆侧偏角和轮胎力非线性观测器，为DYC系统提供精确的车辆状态。本文指出常用的非线性观测器设计方法在车辆系统中实用性的不足，并选择了滑模观测器作为开发车辆状态的非线性观测器；之后详细推导了滑模观测器开发设计方法，并在滑模观测器中加入了系统阻尼项，加速观测状态轨迹收敛，减小观测值颤振；最后基于七自由度车辆模型开发了七阶全维滑模观测器和三阶降维滑模观测器。结果表明，系统阻尼项在观测器中发挥了很好的作用，使车辆状态估计值迅速收敛；全维观测器和降维观测器都达到了非常满意的效果。
之后本文分别从控制车辆侧偏角和控制车辆横摆角速度两个不同的角度开发了DSCDYC系统和DMbDYC系统。DSCDYC系统以车辆侧偏角最小化为控制目标，从稳定性的角度控制车辆；DMbDYC系统以车辆横摆角速度满足驾驶员意图为控制目标，从车辆响应的角度控制车辆。
DSCDYC将车辆侧偏角用于状态反馈，直接控制车辆稳定性。DSCDYC系统采用层次控制架构。上层控制器通过施加整车横摆力矩控制车辆侧偏角。控制车辆侧偏角的车辆控制系统是一个错配系统，因此在上层控制器中使用了针对模型不确定性错配系统开发的先进控制方法：动态面控制方法。下层控制器将整车的横摆力矩作为控制状态，将轮毂电机力矩作为控制输入，并通过对轮胎特性的研究，开发了全新的LoFDDS纵向力分配策略。LoFDDS策略可以精确计算控制边界，兼顾驾驶员的纵向意图，并借助车辆稳态转向特性辅助控制车辆。充分结合IEV车辆的分布式驱动形式，最大化发掘轮胎潜力。DSCDYC系统仿真试验结果显示，DSCDYC系统对车辆侧偏角的抑制作用非常明显，车辆稳定性大幅提升。
DMbDYC系统使用内嵌参考驾驶员模型来预测驾驶员的意图，对驾驶员的操纵失误和滞后有抵制和修正作用。DMbDYC系统解决了现有DYC系统使用方向盘转角来计算驾驶员的意图的不足，因为这种计算方式在驾驶员产生操纵失误或滞后时将变得没有意义。本文在充分理解预瞄驾驶员模型的基础上，对单点预瞄最优侧向加速度驾驶员模型进行了修改和简化，使其实时预测驾驶员意图，并利用驾驶员模型推导了DMbDYC系统的控制目标；之后应用滑模控制方法和LoFDDS策略开发了DMbDYC系统；最后搭建了实时测试平台，并使用软件在环模式对DMbDYC系统进行试验验证。试验结果表明，驾驶员模型能精确预测驾驶员的意图，DMbDYC系统的控制效果比现有控制器更加显著，车辆的响应更符合驾驶员的意图，车辆的稳定性也有很大提升。
本文最后对DYC系统进行试验验证。本文开发了IEV试验车，并进行部件试验和整车试验，获取和验证DYC系统所需参数；之后对已开发DYC系统观测器和控制器相关参数进行设置，并通过IEV车辆验证DYC系统。试验结果表明，试验结果与仿真结果非常接近，DYC系统对车辆稳定性发挥重要作用。
本文主要创新点如下：
1.开发了IEV车辆滑模观测器，在线估计车辆侧偏角和轮胎力。滑模观测器基于七自由度非线性车辆模型开发，内嵌简化UniTire轮胎模型，兼顾模型精确性和实时运算负荷。滑模观测器中还加入系统阻尼项，加速观测器收敛，抑制滑模观测器颤振。
2.开发了针对车辆侧偏角控制的DSCDYC系统。DSCDYC系统应用先进的动态面控制方法，将车辆侧偏角作为反馈控制量，直接对车辆稳定性进行控制，大幅提升了车辆稳定性。
3.开发了LoFDDS纵向力动态分配策略。LoFDDS策略通过精确计算轮胎附着极限来最大化的发掘轮胎潜力，并借助车辆稳态响应特性辅助控制车辆稳定性，同时兼顾车辆的纵向响应也能满足驾驶员意图。
4.提出了全新的DMbDYC系统。DMbDYC系统中内嵌参考驾驶员模型，实时预测驾驶员的意图，改进现有DYC系统控制目标，减轻或抵消驾驶员的反应滞后和误操纵对车辆响应带来的负面影响，提升控制效果。
In the context of the global energy crisis, environmental degradation, and batterytechnology improvements, the electric vehicle (EV) has recently emerged and flourished.The in-wheel motor electric vehicle (IEV) is one form of EV, which is driven by fourin-wheel motors, each of which independently drives one wheel. Since the structure of IEVchanges greatly, the dynamics characteristics and stability control of IEV are of a largechallenge.
Direct yaw moment control (DYC) is an advanced active safety control system focusingon the vehicle stability control. The advantages of developing DYC for IEV are divides intotwo aspects.On one hand, DYC solutes the vehicle stability issues, including the vehiclestates estimation and staibilty control. On the other hand, IEV provides a better platform forDYC. Due to the advantageous structure of IEV, the driving and the combined DYC systemare easily implemented on IEV without any structural alteration. Therefore, the performanceof the DYC system can be upgraded on IEV.
This dissertation develops advanced DYC systems using the model based design(MBD)method for the purpose of vehicle stability improvement. It is funded as a sub program byNational Basic Research Program (Program973)‘Research on Key Basic Issues of HighPerformance In-wheel Motor Electric Vehicles’(No.2011CB711201). The main work of thisdissertation is as follows:
According to the MBD method, a14DOF vehicle dynamics model is built in thisdissertation to provide a simulation platform for the DYC system design. In the14DOFvehicle model, the tire model 'UniTire' by Prof. Guo is utilized in order to improve the modelprecision, and the driver model 'Optimal Preview Lateral Acceleration Driver Model' by Prof.Guo is used to realize the driver-vehicle closed-loop simulation. The validation results show that the vehicle model herein well matches the experimental data. Furthermore, a simplifiedin-wheel motor characteristics model is built, with the parameters identified from thein-wheel motor experimental data.
Two nonlinear vehicle states observers are developed in this dissertation to accuratelyestimate the vehicle slip angle and tire forces. Firstly, the sliding mode observer (SMO) isadopted after the comparison with several popular nonlinear observers, whose feasibility isstrongly restricted in a vehicle system. Secondly, the SMO design methodology is detailedand the system damping terms are added into SMO to derive the higher convergence speed.Finally, a full order SMO (FO-SMO) and a reduced order SMO (RO-SMO) are developedbased on a7DOF vehicle model. The FO-SMO uses the four wheel angular speed as theinputs, while the RO-SMO employs the four longitudinal tire forces as the inputs. The resultsshow that the error dynamics converge fairly fast, and the vehicle slip angle and tire forcesare well estimated by both the FO-SMO and RO-SMO.
The controller design in this dissertation is performed in terms of two differentdirections: the slip angle based control and the yaw rate based control. The slip angle basedcontroller DSCDYC, which is from the angle of vehicle stability, has the control goal ofminimizing the vehicle slip angle. The yaw rate based controller DMbDYC, which is fromthe angle of vehicle response, has the control goal of making the yaw rate meet the driver'sintention.
The hierarchical control architecture is utilized in the DSCDYC system. In the uppercontroller, the desired yaw moment is determined by means of the dynamic surface control(DSC) method, which is proposed based on the sliding mode control. DSC is an advancednonlinear control method for mismatch system and amends the 'term explosion' issue of themultiple sliding surface (MSS) control dealing with the mismatch systems. Furthermore,DSC is a perfect control law for the vehicle slip angle control, since the vehicle system withthe slip angle to be stabilized is a mismatch system. In the lower controller, the longitudinalforces dynamic distribution strategy (LoFDDS) is developed on the basis of the deepanalysis of the tire mechanics. Three major advantages are given by LoFDDS:(1) LoFDDS to some extent ensures the vehicle longitudinal response according with the driver’sintention;(2) LoFDDS makes the vehicle steady state steering characteristics assist tostabilize the vehicle;(3) LoFDDS computes a precise control boundary using an embedded‘UniTire’ tire model. The simulation results show that the vehicle slip angle is perfectlyrestricted by the DSCDYC system, and the vehicle stability is therefore improved greatly.
The current yaw rate based DYC system calculates the driver's intention throughmeasuring the steering wheel angle. However, in some emergency conditions, due to panic,the driver may make an incorrect maneuver. In this case, this method is meaningless,because the steering wheel angle cannot reflect the driver's intention. Unlike common DYCsystem, the DMbDYC system predicts the driver's intention via a driver model. The drivermodel ‘Single Point Preview Optimal Lateral Acceleration Driver Model’ is modified toreal-timely calculate the control goal: the driver’s desired yaw rate. The sliding mode control(SMC) and the LoFDDS strategy are then utilized to complete the DMbDYC system.Subsequently, a general real-time test platform is built, including hardware-in-the-loop (HIL)mode, software-in-the-loop (SIL) mode, and simulator mode. Finally, the SIL mode of theplatform is used to validate the DMbDYC system. The 'virtual vehicle' with the DMbDYCsystem is maneuvered by a real driver. The results show (1) the driver model is able toprecisely predict the driver’s intention;(2) the vehicle response is regulated according to thedriver’s intention by the proposed DMbDYC system;(3) the vehicle stability is greatlyimproved.
The main innovation points of this dissertation are as follows:
1. The sliding mode observer (SMO) for IEV is developed to real-timely estimate theslip angle and tire forces. The SMO embeds the7DOF vehicle model and UniTire model.The system damping terms are added into the nonlinear observer to speed the convergenceand to inhibit the SMO chattering.
2. The DSCDYC system is developed, which directly controls the vehicle slip anglebased on the dynamic surface control (DSC) method. DSC is a perfect control law for thevehicle slip angle control, since the vehicle system with the slip angle to be stabilized is a mismatch system.
3. The LoFDDS strategy is developed to perfect the proposed DSCDYC and DMbDYCsystems. The tire model ‘UniTire’ is embedded in the LoFDDS to precisely compute the tireadhesive limit and to maximally explore the tire potential. Besides, LoFDDS takes advantageof the vehicle steady state characteristics to stabilize the vehicle and ensures the vehiclelongitudinal response according with the driver’s intention.
4. The innovative DMbDYC system, which embeds the driver model, is developed. Bypredicting the driver's intention real-timely, the DMbDYC system improves the currentcontrol target. It reduces the affect of the driver’s mistaken maneuver, and applies the controltorque earlier and timelier.
DYC系统是针对车辆稳定性提出的完备的车辆主动安全控制系统，研究和开发针对IEV车辆稳定性的DYC系统具有两方面的重要意义。一方面，DYC系统可以解决IEV车辆的稳定性问题，包括对IEV车辆重要状态观测和对IEV车辆稳定性控制。另一方面，IEV车辆结构给DYC系统提供了一个更好的平台，DYC系统可以在IEV车辆上实现在传统结构车辆上很难实现的驱动DYC控制或综合DYC控制形式，发挥更好的控制效能，IEV车辆也因此可以获得更高的稳定性。
然而，现有IEV车辆DYC系统研究存在一些不足，如对轮胎状态估计不足，不能充分把握控制边界；直接基于车辆侧偏角控制的研究较少，不能直接控制车辆稳定性；使用方向盘转角估计驾驶员意图，有时可能会导致控制失去意义；前后轮纵向力固定分配，影响控制效果。
针对上述问题，本文依托国家重点基础研究发展计划（973计划）“高性能分布式驱动电动汽车关键基础问题研究（2011CB711201）”，采用基于模型的设计方法（MBD）研究和开发IEV车辆DYC系统。
本文具体研究工作如下：
根据MBD开发流程，本文首先建立了IEV车辆模型，为DYC系统开发提供仿真平台。本文在IEV车辆模型中集成了郭孔辉教授提出的UniTire轮胎模型和最优预瞄侧向加速度驾驶员模型，用以提升模型精度、实现人—车闭环试验仿真。
其次，本文建立了车辆侧偏角和轮胎力非线性观测器，为DYC系统提供精确的车辆状态。本文指出常用的非线性观测器设计方法在车辆系统中实用性的不足，并选择了滑模观测器作为开发车辆状态的非线性观测器；之后详细推导了滑模观测器开发设计方法，并在滑模观测器中加入了系统阻尼项，加速观测状态轨迹收敛，减小观测值颤振；最后基于七自由度车辆模型开发了七阶全维滑模观测器和三阶降维滑模观测器。结果表明，系统阻尼项在观测器中发挥了很好的作用，使车辆状态估计值迅速收敛；全维观测器和降维观测器都达到了非常满意的效果。
之后本文分别从控制车辆侧偏角和控制车辆横摆角速度两个不同的角度开发了DSCDYC系统和DMbDYC系统。DSCDYC系统以车辆侧偏角最小化为控制目标，从稳定性的角度控制车辆；DMbDYC系统以车辆横摆角速度满足驾驶员意图为控制目标，从车辆响应的角度控制车辆。
DSCDYC将车辆侧偏角用于状态反馈，直接控制车辆稳定性。DSCDYC系统采用层次控制架构。上层控制器通过施加整车横摆力矩控制车辆侧偏角。控制车辆侧偏角的车辆控制系统是一个错配系统，因此在上层控制器中使用了针对模型不确定性错配系统开发的先进控制方法：动态面控制方法。下层控制器将整车的横摆力矩作为控制状态，将轮毂电机力矩作为控制输入，并通过对轮胎特性的研究，开发了全新的LoFDDS纵向力分配策略。LoFDDS策略可以精确计算控制边界，兼顾驾驶员的纵向意图，并借助车辆稳态转向特性辅助控制车辆。充分结合IEV车辆的分布式驱动形式，最大化发掘轮胎潜力。DSCDYC系统仿真试验结果显示，DSCDYC系统对车辆侧偏角的抑制作用非常明显，车辆稳定性大幅提升。
DMbDYC系统使用内嵌参考驾驶员模型来预测驾驶员的意图，对驾驶员的操纵失误和滞后有抵制和修正作用。DMbDYC系统解决了现有DYC系统使用方向盘转角来计算驾驶员的意图的不足，因为这种计算方式在驾驶员产生操纵失误或滞后时将变得没有意义。本文在充分理解预瞄驾驶员模型的基础上，对单点预瞄最优侧向加速度驾驶员模型进行了修改和简化，使其实时预测驾驶员意图，并利用驾驶员模型推导了DMbDYC系统的控制目标；之后应用滑模控制方法和LoFDDS策略开发了DMbDYC系统；最后搭建了实时测试平台，并使用软件在环模式对DMbDYC系统进行试验验证。试验结果表明，驾驶员模型能精确预测驾驶员的意图，DMbDYC系统的控制效果比现有控制器更加显著，车辆的响应更符合驾驶员的意图，车辆的稳定性也有很大提升。
本文最后对DYC系统进行试验验证。本文开发了IEV试验车，并进行部件试验和整车试验，获取和验证DYC系统所需参数；之后对已开发DYC系统观测器和控制器相关参数进行设置，并通过IEV车辆验证DYC系统。试验结果表明，试验结果与仿真结果非常接近，DYC系统对车辆稳定性发挥重要作用。
本文主要创新点如下：
1.开发了IEV车辆滑模观测器，在线估计车辆侧偏角和轮胎力。滑模观测器基于七自由度非线性车辆模型开发，内嵌简化UniTire轮胎模型，兼顾模型精确性和实时运算负荷。滑模观测器中还加入系统阻尼项，加速观测器收敛，抑制滑模观测器颤振。
2.开发了针对车辆侧偏角控制的DSCDYC系统。DSCDYC系统应用先进的动态面控制方法，将车辆侧偏角作为反馈控制量，直接对车辆稳定性进行控制，大幅提升了车辆稳定性。
3.开发了LoFDDS纵向力动态分配策略。LoFDDS策略通过精确计算轮胎附着极限来最大化的发掘轮胎潜力，并借助车辆稳态响应特性辅助控制车辆稳定性，同时兼顾车辆的纵向响应也能满足驾驶员意图。
4.提出了全新的DMbDYC系统。DMbDYC系统中内嵌参考驾驶员模型，实时预测驾驶员的意图，改进现有DYC系统控制目标，减轻或抵消驾驶员的反应滞后和误操纵对车辆响应带来的负面影响，提升控制效果。
In the context of the global energy crisis, environmental degradation, and batterytechnology improvements, the electric vehicle (EV) has recently emerged and flourished.The in-wheel motor electric vehicle (IEV) is one form of EV, which is driven by fourin-wheel motors, each of which independently drives one wheel. Since the structure of IEVchanges greatly, the dynamics characteristics and stability control of IEV are of a largechallenge.
Direct yaw moment control (DYC) is an advanced active safety control system focusingon the vehicle stability control. The advantages of developing DYC for IEV are divides intotwo aspects.On one hand, DYC solutes the vehicle stability issues, including the vehiclestates estimation and staibilty control. On the other hand, IEV provides a better platform forDYC. Due to the advantageous structure of IEV, the driving and the combined DYC systemare easily implemented on IEV without any structural alteration. Therefore, the performanceof the DYC system can be upgraded on IEV.
This dissertation develops advanced DYC systems using the model based design(MBD)method for the purpose of vehicle stability improvement. It is funded as a sub program byNational Basic Research Program (Program973)‘Research on Key Basic Issues of HighPerformance In-wheel Motor Electric Vehicles’(No.2011CB711201). The main work of thisdissertation is as follows:
According to the MBD method, a14DOF vehicle dynamics model is built in thisdissertation to provide a simulation platform for the DYC system design. In the14DOFvehicle model, the tire model 'UniTire' by Prof. Guo is utilized in order to improve the modelprecision, and the driver model 'Optimal Preview Lateral Acceleration Driver Model' by Prof.Guo is used to realize the driver-vehicle closed-loop simulation. The validation results show that the vehicle model herein well matches the experimental data. Furthermore, a simplifiedin-wheel motor characteristics model is built, with the parameters identified from thein-wheel motor experimental data.
Two nonlinear vehicle states observers are developed in this dissertation to accuratelyestimate the vehicle slip angle and tire forces. Firstly, the sliding mode observer (SMO) isadopted after the comparison with several popular nonlinear observers, whose feasibility isstrongly restricted in a vehicle system. Secondly, the SMO design methodology is detailedand the system damping terms are added into SMO to derive the higher convergence speed.Finally, a full order SMO (FO-SMO) and a reduced order SMO (RO-SMO) are developedbased on a7DOF vehicle model. The FO-SMO uses the four wheel angular speed as theinputs, while the RO-SMO employs the four longitudinal tire forces as the inputs. The resultsshow that the error dynamics converge fairly fast, and the vehicle slip angle and tire forcesare well estimated by both the FO-SMO and RO-SMO.
The controller design in this dissertation is performed in terms of two differentdirections: the slip angle based control and the yaw rate based control. The slip angle basedcontroller DSCDYC, which is from the angle of vehicle stability, has the control goal ofminimizing the vehicle slip angle. The yaw rate based controller DMbDYC, which is fromthe angle of vehicle response, has the control goal of making the yaw rate meet the driver'sintention.
The hierarchical control architecture is utilized in the DSCDYC system. In the uppercontroller, the desired yaw moment is determined by means of the dynamic surface control(DSC) method, which is proposed based on the sliding mode control. DSC is an advancednonlinear control method for mismatch system and amends the 'term explosion' issue of themultiple sliding surface (MSS) control dealing with the mismatch systems. Furthermore,DSC is a perfect control law for the vehicle slip angle control, since the vehicle system withthe slip angle to be stabilized is a mismatch system. In the lower controller, the longitudinalforces dynamic distribution strategy (LoFDDS) is developed on the basis of the deepanalysis of the tire mechanics. Three major advantages are given by LoFDDS:(1) LoFDDS to some extent ensures the vehicle longitudinal response according with the driver’sintention;(2) LoFDDS makes the vehicle steady state steering characteristics assist tostabilize the vehicle;(3) LoFDDS computes a precise control boundary using an embedded‘UniTire’ tire model. The simulation results show that the vehicle slip angle is perfectlyrestricted by the DSCDYC system, and the vehicle stability is therefore improved greatly.
The current yaw rate based DYC system calculates the driver's intention throughmeasuring the steering wheel angle. However, in some emergency conditions, due to panic,the driver may make an incorrect maneuver. In this case, this method is meaningless,because the steering wheel angle cannot reflect the driver's intention. Unlike common DYCsystem, the DMbDYC system predicts the driver's intention via a driver model. The drivermodel ‘Single Point Preview Optimal Lateral Acceleration Driver Model’ is modified toreal-timely calculate the control goal: the driver’s desired yaw rate. The sliding mode control(SMC) and the LoFDDS strategy are then utilized to complete the DMbDYC system.Subsequently, a general real-time test platform is built, including hardware-in-the-loop (HIL)mode, software-in-the-loop (SIL) mode, and simulator mode. Finally, the SIL mode of theplatform is used to validate the DMbDYC system. The 'virtual vehicle' with the DMbDYCsystem is maneuvered by a real driver. The results show (1) the driver model is able toprecisely predict the driver’s intention;(2) the vehicle response is regulated according to thedriver’s intention by the proposed DMbDYC system;(3) the vehicle stability is greatlyimproved.
The main innovation points of this dissertation are as follows:
1. The sliding mode observer (SMO) for IEV is developed to real-timely estimate theslip angle and tire forces. The SMO embeds the7DOF vehicle model and UniTire model.The system damping terms are added into the nonlinear observer to speed the convergenceand to inhibit the SMO chattering.
2. The DSCDYC system is developed, which directly controls the vehicle slip anglebased on the dynamic surface control (DSC) method. DSC is a perfect control law for thevehicle slip angle control, since the vehicle system with the slip angle to be stabilized is a mismatch system.
3. The LoFDDS strategy is developed to perfect the proposed DSCDYC and DMbDYCsystems. The tire model ‘UniTire’ is embedded in the LoFDDS to precisely compute the tireadhesive limit and to maximally explore the tire potential. Besides, LoFDDS takes advantageof the vehicle steady state characteristics to stabilize the vehicle and ensures the vehiclelongitudinal response according with the driver’s intention.
4. The innovative DMbDYC system, which embeds the driver model, is developed. Bypredicting the driver's intention real-timely, the DMbDYC system improves the currentcontrol target. It reduces the affect of the driver’s mistaken maneuver, and applies the controltorque earlier and timelier.
引文
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