车辆速度估计非线性观测器方法研究
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摘要
随着汽车保有量的增加,汽车的操纵稳定性和主动安全性问题受到广泛关注。汽车主动安全性控制系统可有效提高汽车的操纵稳定性,避免交通事故的发生。但这些汽车主动安全性系统可有效实施各种控制逻辑的前提是准确的获得车辆的行驶状态,包括汽车的纵向速度、侧向速度、质心侧偏角及横摆角速度等状态信息。目前上述车辆状态信息在批量生产的汽车上无法通过车载传感器直接测量得到。车辆状态信息的缺失,限制了汽车主动安全控制技术的发展,并已成为制约汽车主动安全控制系统发展的瓶颈问题。随着估计理论的发展,利用车辆上已装备的传感器获得的车辆状态信息,进行车辆行驶状态估计成为研究热点,但同时由于汽车行驶过程中环境变化迅速,道路情况极其复杂,车载传感器存在着标定误差和温度漂移误差,这些因素也使得车辆行驶状态估计成为一项极具挑战性的工作。在众多待估计的车辆行驶状态中,车辆的纵向速度和侧向速度是车辆主动安全性控制系统发挥作用的必备信息,这使得纵向车速和侧向车速的估计问题具有重要的理论意义和工程应用价值。
本文主要研究内容是针对车辆主动安全控制问题中纵向车速和侧向车速不可通过传感器测量问题,研究可靠、实时的车辆速度估计非线性观测器设计方法,在搭建的车辆速度估计硬件在环仿真平台上,对车速估计效果进行实验验证,并讨论了车速观测器的硬件实现方案。
首先针对车辆运行过程中表现出的非线性动态特性,基于车辆动力学模型和Uni-Tire轮胎模型讨论了采用较少测量信息的非线性全维观测器方法对车辆速度进行估计的问题。在得到纵滑-侧偏联合工况下Uni-Tire轮胎模型的参数后,利用Uni-Tire轮胎模型计算得到的加速度替代传感器的测量信息,构造车辆动力学模型。然后根据车载传感器测量得到的轮速、侧向加速度及横摆角速度信息构造非线性全维观测器,并在输入-状态稳定性理论框架下对观测器的稳定性进行了分析,并由此进一步得到了非线性全维车速观测器增益满足的条件。所得到的非线性全维车速观测器结构简单,实时性好,易于实现。
针对车辆系统结构复杂、状态变量耦合严重且非线性较强的问题,同时考虑质心变化对车辆动力学模型的影响,提出计算量较小的车辆速度非线性降阶观测器估计方法。通过分析横摆角速度与车辆纵向速度、侧向速度之间的动力学关系,以横摆角速度偏差作为车辆速度估计的校正项,构造非线性降阶车速观测器;在保证降阶观测器ISS稳定的同时,得到了非线性降阶观测器增益满足的条件,并利用多胞型模型描述及其相应的变换将其转化为LMIs描述;进一步通过分析观测器中的参数与误差衰减速度、稳态误差之间的关系,得到了降阶观测器的求解步骤。将降阶观测器应用于车辆运行的常规和极限工况仿真,并通过实时实验验证了降阶观测器的实时性。
为避免复杂轮胎模型所带来的运算负担,进一步提高车速观测器的计算速度,建立MAP/机理混合描述的轮胎模型。结合车辆动力学分析,在纵向车速观测器设计时,将科氏加速度作为干扰,从而提出车辆速度估计非线性级联观测器方法。首先采用轮速信息构造纵向车速观测器,其次以纵向速度估计值作为侧向车速观测器的输入,设计侧向车速观测器,二者构成了级联结构;再次借助于ISS理论对级联车速观测器的稳定性进行分析,得到级联观测器增益满足的条件;最后,为确定车速观测器增益及参数选取范围,提出非线性级联车速观测器评价的性能指标,采用随机算法通过蒙特卡罗实验对非线性级联车速观测器参数选取范围进行讨论。
为验证非线性车速估计方法的有效性,需要进行实验研究,本文在利用xPC-Target实时仿真结构和车辆动力学软件veDYNA构建的车辆速度估计HiL仿真台架上,通过对方向盘、油门踏板和制动踏板外部实物的操作,对非线性车辆速度观测器方法进行硬件在环实验研究。在得到较好实验效果的基础上,为满足小型化,实时性要求,采用FPGA/SOPC方法讨论了观测器硬件实现方案,并通过dSPACE实时仿真系统和FPGA开发板对车速观测器硬件实现方案进行了实验验证并取得了较好的实验效果。
论文对所提出的各种方法都进行了明确的论证,并针对相应的观测器设计过程给出了较为详尽的推导过程。为了验证本文所提出的方法的有效性,每种车速估计算法都进行了仿真研究及实时性实验。本文从车辆系统建模,车辆速度观测器设计,观测器参数选取和仿真实验等方面都给出了详细的分析和讨论。结果表明,文中所提的车速估计方法整体效果是令人满意的。
本论文的研究工作也遗留了一些问题,例如车辆模型建模过程中由于忽略了侧倾、风阻等因素的影响,使得模型存在一定的建模误差,这就需要在以后的工作中不断提高车辆动力学模型的精度;在降阶观测器设计时仅采用横摆角速度的变化率作为校正项,由于轮速可直接通过传感器测量并且可通过驱动力矩和制动力矩建模,因此,可以采用7自由度车辆模型设计车辆速度降阶观测器;在车辆速度观测器FPGA/SOPC硬件实现研究中,可以设计相应的硬件加速器进一步提高硬件实现的速度;在车辆系统HiL仿真平台搭建问题上,目前只嵌入了驾驶员操纵部分,如何嵌入其他有助于车辆速度估计的外部传感器信号,还有待进一步研究。
With the increment of urban vehicle ownership, vehicle handling stability and activesafety issues received extensive attention. Active safety control systems can improvethe handling stability of vehicle e?ectively and then avoid tra?c accidents. However,on the premise that we can access the vehicle running states accurately, which includethe longitudinal vehicle velocity, the lateral vehicle velocity, the sideslip angle, the yawrate and other states information, then the control logic of these vehicle active safetysystems can be work e?ectively. At present, the vehicle states that mentioned abovecan not be measured directly by the onboard sensors on the mass production vehicles.It has become bottleneck issues and limited the development of vehicle active safetycontrol systems because the lack of vehicle states information. With the developmentof the estimation theory, the vehicle states estimation become focus problems using themeasured information by the onboard sensors which has been equipped on the massproduction vehicle. Meanwhile, the vehicle states estimation is a challenging work becausethe environment change rapidly in the vehicle running and the road situation is extremelycomplex, in addition, there are calibration errors and temperature drift errors in theonboard sensors. The longitudinal vehicle velocity and lateral vehicle velocity are theessential information to be estimated among the numerous vehicle states for the activesafety systems. Therefore, the longitudinal vehicle velocity and lateral vehicle velocityhave important theoretical and practical significance.
The objective of this paper is to present reliable and real-time nonlinear observermethod for vehicle velocity estimation for the longitudinal vehicle velocity and lateralvehicle velocity, which can not be measured directly in the active safety control problem.The experiments are carried out to validate the estimation results on the hardware-in-the-loop simulation platform, and then the hardware implementation scheme of nonlinearobserver is discussed.
For the nonlinear dynamic characteristics shown in the vehicle running, A nonlinearfull-order observer with less measurement information is proposed for vehicle velocity es- timation based on the vehicle dynamic model and Uni-Tire model for longitudinal slipand lateral slip. The computed acceleration information using Uni-Tire model replace theonboard sensor information after identification the Uni-Tire model for longitudinal slipand lateral slip. The longitudinal velocity, lateral velocity and yaw rate of the vehicleare estimated by the observer using the information of vehicle states such as wheel ro-tational speed, the steering wheel angle and lateral acceleration which are measured byon-board sensors. The stability of the observer is analyzed using the theory of input-to-state stability(ISS), furthermore, the condition which the observer gain stratified is got.The nonlinear full-order observer has simple structure, good real time performance andcan be realized easily.
For the complex structure, the state coupled with each other and the strong nonlinear-ity of vehicle systems, a nonlinear reduced-order observer method with less computationis presented for the longitudinal vehicle velocity and lateral vehicle velocity estimation,where the impact on vehicle dynamics is considered, which is caused by the changes ofCoG in the vehicle running. The yaw acceleration is chosen as the correction informationfor longitudinal vehicle velocity and lateral vehicle velocity estimation by analyzing thedynamic relationship between yaw rate and vehicle velocity. The condition of nonlinearobserver gain satisfied is obtained under the situation that the reduce-order observer isISS, and the condition is transform into LMIs using the Polytopic model description. Thesolving steps of reduce order observer is received by analyzing the relationship betweenobserver parameters, error decay rate and steady state error. The simulation study for es-timation results of reduced-order observer is carried out in the conventional condition andcritical condition, and the real-time experiments are carried out to validate the real-timeperformance.
In order to avoid computational burden caused by complex tire model and improvethe calculation speed of the vehicle velocities observer, the tire model is received whichis built using MAP and the mechanism model description. The nonlinear cascaded ob-server method is presented for vehicle longitudinal velocity and lateral velocity estimationconsidering coriolis acceleration as disturbance of longitudinal vehicle velocity observer.we first used wheel rotational speed build longitudinal vehicle velocity observer, and thenthe estimated longitudinal vehicle velocity is used as input to estimated lateral vehiclevelocity. The longitudinal vehicle velocity observer and lateral vehicle velocity observercomposed of cascade structure. The ISS theory is used to analyse the stability of the ob-server and the condition which observer gain satisfied is got. Finally, in order to determinethe range of the observer gain and parameters, the performance function for nonlinearcascade observer is proposed, and the randomized algorithms is employed to discuss the range of the observer gain and parameters using Monte Carlo experiments.
In order to validate the effectiveness of the nonlinear vehicle velocity observer method,the experiment must be carried out. The nonlinear vehicle velocity observer is validatedon the HiL platform which is builded based on xPC-Target real-time structure and vehi-cle dynamics software by operating the external steering wheel angle, acceleration pedaland brake pedal. Based on this, the FPGA/SOPC scheme is proposed for the hard-ware implementation of nonlinear vehicle velocity observer to satisfy the requirement ofminiaturization, real-time performance. The experimental validation is carried out for theeffectiveness and real-time performance base on dSPACE real time platform and FPGAexploited board and better experiment result is obtained.
The formulation processes and the proof of mentioned approaches are presented indetail in this thesis. Moreover, in order to validate the efficiency of the proposed ap-proaches, we give simulation results for each approach, which is discussed from systemmodeling, vehicle velocity observer design, observer parameter choosing, simulation andexperiments. The simulation and experiments results indicate that estimation methodeffects with the proposed approaches are satisfactory.
Deeper research work needs to be done since some problems are still remain to besolved, for example, the roll motion and aerodynamic are omitted during the vehiclemodeling, so there exist some modeling errors, It requires improving the accuracy ofvehicle dynamics model constantly in future work. As the wheel speed can be measureddirectly by onboard sensors and it can be modeled by the drive torque and brake torque, wecan try to use the 7 degrees of freedom vehicle dynamics model to design the reduce-orderobserver. We can design some hardware accelerators to increase the computation speedin the research of FPGA/SOPC hardware implementation of nonlinear vehicle velocityobserver. In the hardware platform, only the hardware of driver manoeuvre is embeddedat present, how to embed more external sensor information which is useful for vehiclestates estimation, it is need to be further research.
本文主要研究内容是针对车辆主动安全控制问题中纵向车速和侧向车速不可通过传感器测量问题,研究可靠、实时的车辆速度估计非线性观测器设计方法,在搭建的车辆速度估计硬件在环仿真平台上,对车速估计效果进行实验验证,并讨论了车速观测器的硬件实现方案。
首先针对车辆运行过程中表现出的非线性动态特性,基于车辆动力学模型和Uni-Tire轮胎模型讨论了采用较少测量信息的非线性全维观测器方法对车辆速度进行估计的问题。在得到纵滑-侧偏联合工况下Uni-Tire轮胎模型的参数后,利用Uni-Tire轮胎模型计算得到的加速度替代传感器的测量信息,构造车辆动力学模型。然后根据车载传感器测量得到的轮速、侧向加速度及横摆角速度信息构造非线性全维观测器,并在输入-状态稳定性理论框架下对观测器的稳定性进行了分析,并由此进一步得到了非线性全维车速观测器增益满足的条件。所得到的非线性全维车速观测器结构简单,实时性好,易于实现。
针对车辆系统结构复杂、状态变量耦合严重且非线性较强的问题,同时考虑质心变化对车辆动力学模型的影响,提出计算量较小的车辆速度非线性降阶观测器估计方法。通过分析横摆角速度与车辆纵向速度、侧向速度之间的动力学关系,以横摆角速度偏差作为车辆速度估计的校正项,构造非线性降阶车速观测器;在保证降阶观测器ISS稳定的同时,得到了非线性降阶观测器增益满足的条件,并利用多胞型模型描述及其相应的变换将其转化为LMIs描述;进一步通过分析观测器中的参数与误差衰减速度、稳态误差之间的关系,得到了降阶观测器的求解步骤。将降阶观测器应用于车辆运行的常规和极限工况仿真,并通过实时实验验证了降阶观测器的实时性。
为避免复杂轮胎模型所带来的运算负担,进一步提高车速观测器的计算速度,建立MAP/机理混合描述的轮胎模型。结合车辆动力学分析,在纵向车速观测器设计时,将科氏加速度作为干扰,从而提出车辆速度估计非线性级联观测器方法。首先采用轮速信息构造纵向车速观测器,其次以纵向速度估计值作为侧向车速观测器的输入,设计侧向车速观测器,二者构成了级联结构;再次借助于ISS理论对级联车速观测器的稳定性进行分析,得到级联观测器增益满足的条件;最后,为确定车速观测器增益及参数选取范围,提出非线性级联车速观测器评价的性能指标,采用随机算法通过蒙特卡罗实验对非线性级联车速观测器参数选取范围进行讨论。
为验证非线性车速估计方法的有效性,需要进行实验研究,本文在利用xPC-Target实时仿真结构和车辆动力学软件veDYNA构建的车辆速度估计HiL仿真台架上,通过对方向盘、油门踏板和制动踏板外部实物的操作,对非线性车辆速度观测器方法进行硬件在环实验研究。在得到较好实验效果的基础上,为满足小型化,实时性要求,采用FPGA/SOPC方法讨论了观测器硬件实现方案,并通过dSPACE实时仿真系统和FPGA开发板对车速观测器硬件实现方案进行了实验验证并取得了较好的实验效果。
论文对所提出的各种方法都进行了明确的论证,并针对相应的观测器设计过程给出了较为详尽的推导过程。为了验证本文所提出的方法的有效性,每种车速估计算法都进行了仿真研究及实时性实验。本文从车辆系统建模,车辆速度观测器设计,观测器参数选取和仿真实验等方面都给出了详细的分析和讨论。结果表明,文中所提的车速估计方法整体效果是令人满意的。
本论文的研究工作也遗留了一些问题,例如车辆模型建模过程中由于忽略了侧倾、风阻等因素的影响,使得模型存在一定的建模误差,这就需要在以后的工作中不断提高车辆动力学模型的精度;在降阶观测器设计时仅采用横摆角速度的变化率作为校正项,由于轮速可直接通过传感器测量并且可通过驱动力矩和制动力矩建模,因此,可以采用7自由度车辆模型设计车辆速度降阶观测器;在车辆速度观测器FPGA/SOPC硬件实现研究中,可以设计相应的硬件加速器进一步提高硬件实现的速度;在车辆系统HiL仿真平台搭建问题上,目前只嵌入了驾驶员操纵部分,如何嵌入其他有助于车辆速度估计的外部传感器信号,还有待进一步研究。
With the increment of urban vehicle ownership, vehicle handling stability and activesafety issues received extensive attention. Active safety control systems can improvethe handling stability of vehicle e?ectively and then avoid tra?c accidents. However,on the premise that we can access the vehicle running states accurately, which includethe longitudinal vehicle velocity, the lateral vehicle velocity, the sideslip angle, the yawrate and other states information, then the control logic of these vehicle active safetysystems can be work e?ectively. At present, the vehicle states that mentioned abovecan not be measured directly by the onboard sensors on the mass production vehicles.It has become bottleneck issues and limited the development of vehicle active safetycontrol systems because the lack of vehicle states information. With the developmentof the estimation theory, the vehicle states estimation become focus problems using themeasured information by the onboard sensors which has been equipped on the massproduction vehicle. Meanwhile, the vehicle states estimation is a challenging work becausethe environment change rapidly in the vehicle running and the road situation is extremelycomplex, in addition, there are calibration errors and temperature drift errors in theonboard sensors. The longitudinal vehicle velocity and lateral vehicle velocity are theessential information to be estimated among the numerous vehicle states for the activesafety systems. Therefore, the longitudinal vehicle velocity and lateral vehicle velocityhave important theoretical and practical significance.
The objective of this paper is to present reliable and real-time nonlinear observermethod for vehicle velocity estimation for the longitudinal vehicle velocity and lateralvehicle velocity, which can not be measured directly in the active safety control problem.The experiments are carried out to validate the estimation results on the hardware-in-the-loop simulation platform, and then the hardware implementation scheme of nonlinearobserver is discussed.
For the nonlinear dynamic characteristics shown in the vehicle running, A nonlinearfull-order observer with less measurement information is proposed for vehicle velocity es- timation based on the vehicle dynamic model and Uni-Tire model for longitudinal slipand lateral slip. The computed acceleration information using Uni-Tire model replace theonboard sensor information after identification the Uni-Tire model for longitudinal slipand lateral slip. The longitudinal velocity, lateral velocity and yaw rate of the vehicleare estimated by the observer using the information of vehicle states such as wheel ro-tational speed, the steering wheel angle and lateral acceleration which are measured byon-board sensors. The stability of the observer is analyzed using the theory of input-to-state stability(ISS), furthermore, the condition which the observer gain stratified is got.The nonlinear full-order observer has simple structure, good real time performance andcan be realized easily.
For the complex structure, the state coupled with each other and the strong nonlinear-ity of vehicle systems, a nonlinear reduced-order observer method with less computationis presented for the longitudinal vehicle velocity and lateral vehicle velocity estimation,where the impact on vehicle dynamics is considered, which is caused by the changes ofCoG in the vehicle running. The yaw acceleration is chosen as the correction informationfor longitudinal vehicle velocity and lateral vehicle velocity estimation by analyzing thedynamic relationship between yaw rate and vehicle velocity. The condition of nonlinearobserver gain satisfied is obtained under the situation that the reduce-order observer isISS, and the condition is transform into LMIs using the Polytopic model description. Thesolving steps of reduce order observer is received by analyzing the relationship betweenobserver parameters, error decay rate and steady state error. The simulation study for es-timation results of reduced-order observer is carried out in the conventional condition andcritical condition, and the real-time experiments are carried out to validate the real-timeperformance.
In order to avoid computational burden caused by complex tire model and improvethe calculation speed of the vehicle velocities observer, the tire model is received whichis built using MAP and the mechanism model description. The nonlinear cascaded ob-server method is presented for vehicle longitudinal velocity and lateral velocity estimationconsidering coriolis acceleration as disturbance of longitudinal vehicle velocity observer.we first used wheel rotational speed build longitudinal vehicle velocity observer, and thenthe estimated longitudinal vehicle velocity is used as input to estimated lateral vehiclevelocity. The longitudinal vehicle velocity observer and lateral vehicle velocity observercomposed of cascade structure. The ISS theory is used to analyse the stability of the ob-server and the condition which observer gain satisfied is got. Finally, in order to determinethe range of the observer gain and parameters, the performance function for nonlinearcascade observer is proposed, and the randomized algorithms is employed to discuss the range of the observer gain and parameters using Monte Carlo experiments.
In order to validate the effectiveness of the nonlinear vehicle velocity observer method,the experiment must be carried out. The nonlinear vehicle velocity observer is validatedon the HiL platform which is builded based on xPC-Target real-time structure and vehi-cle dynamics software by operating the external steering wheel angle, acceleration pedaland brake pedal. Based on this, the FPGA/SOPC scheme is proposed for the hard-ware implementation of nonlinear vehicle velocity observer to satisfy the requirement ofminiaturization, real-time performance. The experimental validation is carried out for theeffectiveness and real-time performance base on dSPACE real time platform and FPGAexploited board and better experiment result is obtained.
The formulation processes and the proof of mentioned approaches are presented indetail in this thesis. Moreover, in order to validate the efficiency of the proposed ap-proaches, we give simulation results for each approach, which is discussed from systemmodeling, vehicle velocity observer design, observer parameter choosing, simulation andexperiments. The simulation and experiments results indicate that estimation methodeffects with the proposed approaches are satisfactory.
Deeper research work needs to be done since some problems are still remain to besolved, for example, the roll motion and aerodynamic are omitted during the vehiclemodeling, so there exist some modeling errors, It requires improving the accuracy ofvehicle dynamics model constantly in future work. As the wheel speed can be measureddirectly by onboard sensors and it can be modeled by the drive torque and brake torque, wecan try to use the 7 degrees of freedom vehicle dynamics model to design the reduce-orderobserver. We can design some hardware accelerators to increase the computation speedin the research of FPGA/SOPC hardware implementation of nonlinear vehicle velocityobserver. In the hardware platform, only the hardware of driver manoeuvre is embeddedat present, how to embed more external sensor information which is useful for vehiclestates estimation, it is need to be further research.
引文
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