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类型 应用研究 预答辩日期 2017-11-22
开始(开题)日期 2014-09-11 论文结束日期 2017-09-05
地点 机械楼南高厅 论文选题来源 973、863项目     论文字数 6.6 (万字)
题目 分布式驱动电动汽车状态参数估计与侧向稳定性鲁棒控制研究
主题词 分布式驱动电动汽车,状态参数估计,容积卡尔曼滤波,侧向稳定性,鲁棒控制
摘要 与集中式驱动电动汽车相比,分布式驱动电动汽车使用轮毂电机直接驱动四个车轮,以线控系统(X-by-wire,X代表驱动、制动等)取代传统的机械传动链接,在大幅简化底盘结构、提高传动效率的同时,可实现各车轮转矩的独立控制与快速响应,为车辆动力学控制提供了独特的优势(例如,容易产生需要的横摆力矩),更易实现车辆底盘侧向动力学主动安全系统(前轮主动转向系统AFS、直接横摆力矩控制系统DYC等)的集成控制,将极大地改善车辆操纵舒适性和紧急转向工况下车辆侧向稳定性。然而,准确而实时地获得电动汽车行驶过程中的状态参数信息是实现车辆底盘侧向动力学主动安全控制的前提与必要条件,同时先进的控制技术是发挥分布式驱动电动汽车独立驱动优势实现车辆底盘动力学侧向稳定性控制的关键。本文以分布式轮毂驱动电动汽车为研究对象,围绕电动汽车侧向动力学系统的状态参数非线性估计和侧向稳定性鲁棒控制策略等问题展开研究,论文的研究主要内容如下: (1)深入研究三阶球面-相径容积准则求解贝叶斯滤波中的“非线性函数×高斯密度”问题,将全新高斯域贝叶斯非线性滤波框架下的容积卡尔曼滤波理论引入车辆动力学系统状态估计中,利用分布式驱动电动汽车提供的标准车载信息测量量,设计车辆纵向速度、侧向速度、质心侧偏角等车辆状态容积卡尔曼滤波估计算法,在CarSim/Matlab环境中开发了高保真的分布式轮毂驱动电动汽车CarSim 和 Simulink联合仿真平台,仿真验证了容积卡尔曼滤波理论在车辆动力学系统状态估计中的可行性与适应性。 (2)为实时估计车辆行驶过程中的质心侧倾角等侧倾状态及轮胎与路面之间相互作用的轮胎侧向力、路面附着系数等参数,采用非稳态效应的Dugoff动态轮胎模型刻画轮胎瞬时力学特性,设计分布式驱动电动汽车双容积卡尔曼滤波车辆状态参数联合估计理论框架,其中第一个容积卡尔曼滤波估计器估计车辆运行的速度、车辆质心侧倾角、轮胎侧向力等状态,另一个串联的容积卡尔曼滤波估计器估计路面附着系数;同时,为有效地提高双CKF状态参数联合估计的实时性、精度和稳定性,在CKF估计过程中直接以协方差矩阵的平方根进行迭代更新,推导了平方根双容积卡尔曼滤波的车辆状态参数联合估计的算法流程,仿真验证双CKF估计算法能对车辆状态参数进行在线估计,且具有较高的估计精度。 (3)利用相平面法分析车辆横摆动力学系统的非线性运动稳定性,将车辆的横摆运动张成质心侧偏角-横摆角速度的相空间,构建了以非稳定平衡点-鞍点为临界稳定边界的相平面稳定域来分析车辆横摆稳定性,考察路面附着系数、方向盘转角、车辆纵向速度等重要因素对车辆横摆运动稳定性的影响。针对分布式驱动电动汽车侧向动力学系统的不确定性问题,将能应对参数摄动的不确定鲁棒 控制技术引入车辆侧向动力学系统,采用范数描述了轮胎侧偏刚度、车辆纵向速度、车辆惯性量等参数的不确定性,发展了面向电动汽车AFS和DYC集成系统定向控制的不确定车辆侧向动力学模型,构建了基于动态误差变量的不确定电动汽车侧向动力学横摆运动增广系统,推导了车辆闭环系统渐近稳定的 反馈控制器的成立条件,完成了AFS和DYC系统的鲁棒 集成控制器设计,仿真验证了鲁棒控制器能利用左右轮毂电机转矩差提高车辆行驶过程中的侧向稳定性。 (4)为提高车辆转向操纵过程中的侧倾稳定性,根据定义的车辆载荷参数、车辆质心侧倾角和临界侧向加速度组合的侧倾稳定指标对车辆横摆角速度名义值进行修正,发展了面向主动侧倾稳定性定向控制的不确定电动汽车侧倾动力学系统模型。考虑执行器饱和特性,在抗饱和问题广义 控制系统的统一框架下,采用Lyapunov理论设计了车辆主动侧倾稳定性抗饱和鲁棒控制器,根据Finsler 递归定理推导了车辆主动侧倾稳定性抗饱和鲁棒反馈控制器存在的条件,使电动汽车主动侧倾动力学闭环系统满足渐近稳定且具有期望的控制性能指标,仿真验证了抗饱和主动侧倾鲁棒控制的车辆在转向过程中具有较大的侧倾稳定裕度,能避免车身姿态侧倾过大导致的车辆不安全甚至失稳。 (5)对分布式驱动轮毂电动汽车进行实车路面试验研究,在低速下采用J转向和蛇形试验对车辆状态参数的估计进行了验证试验,采用半圆转向和两种长时间历程的连续激烈转向试验对车辆侧向稳定性控制系统进行验验证,试验结果表明,设计的车辆状态参数估计算法能较精确的估计车辆的实时状态参数,发展的车辆鲁棒侧向稳定性控制策略能有效保证车辆侧向运动过程中的稳定性,试验验证了研究的状态参数估计算法和鲁棒控制策略的有效性和可行性。
英文题目 Parameter Estimation and Robust Control of Lateral Stability for Distributed Drive Electric Vehicles
英文主题词 Distributed drive electric vehicles,State and parameter estimation,Cubature kalman filter,Lateral stability, Robust control
英文摘要 Compared with centralized drive electric vehicles, the mechanical link between the driver’s action and actuator of distributed drive electric vehicles (DDEV) has been removed and replaced with X-by-wire system (e.g., drive-by-wire and brake-by-wire), and distributed drive electric vehicles utilize in-wheel motors to drive the wheels such that the torque of each wheel can be controlled independently and fast, which significantly simplify the traditional vehicle structures aand improve transmission efficiency, and further it provides unique advantage with more flexibilities in vehicle dynamics control (e.g.,generate the external yaw moment). The the direct yaw control system (DYC) provided by steer-by-wire technique, together with active front steering system (AFS), possesses potentiality to improve vehicle handling performance and lateral stability of distributed drive electric vehicles. However, performance and stability of vehicle motion control systems heavily depend on accurate knowledge of important vehicle parameters,meanwhile, advanced control technology in vehicle lateral dynamics control systems is also very crucial for enhancing vehicle stability and handling performance of distributed drive electric vehicles.With regard to distributed drive electric vehicles, this dissertation studied parameter estimation and lateral stability with robust control strategy for the lateral dynamic system, the main contents are as follows: (1) Research the problem of "nonlinear function × gaussian density" in bayesian filtering solved with third-order spherical-radial cubature criterion, the new cubature kalman filter theory under gaussian bayesian nonlinear filtering framework is introduced into the vehicle dynamics state estimation system, the CKF estimation algorithm is designed to estimate longitudinal velocity, lateral velocity and vehicle sideslip angle utilizing real-time measurements of in-vehicle sensors in distributed drive electric vehicles. And then the high-fidelity co-simulation platform between Carsim and Matlab/Simulink for the DDEV is established, simulations evaluate the performance of the designed CKF estimation. (2)To real-time estimate vehicle roll angle,lateral tire-road forces and tire-road friction coefficient, the nonlinear Dugoff dynamic tire model is applied to describe transient characteristics,dual CKF is designed to jointly estimate vehicle state and parameter for DDEV, the first CKF estimate vehicle velocity, vehicle roll angle,lateral tire-road forces while the second CKF estimate tire-road friction coefficient based on estimated vehicle states from the first CKF.In order to effectively improve the real-time, accuracy and stability of the joint estimation in dual CKF, the square root cubature kalman filter is also applied.Simulation is implemented to evaluate the performance of the proposed dual CKF estimation. (3)The phase plane approach is employed to analyze the nonlinear motion stability in vehicle yaw dynamics system,and the the phase space about vehicle yaw motion is plotted as vehicle sideslip angle and yaw rate, and then the lateral stability region where critical stable boundary depends on the unsteady equilibrium point-saddle point is analyzed in term of tire-road friction coefficient,steering wheel angle and longitudinal velocity.Uncertain factors such as tire cornering stiffness and vehicle mass in vehicle lateral dynamics are represented via the norm uncertainty. To address the importance of time-varying longitudinal velocity for vehicle lateral stability control, uncertainty about longitudinal velocity is also considered.Combined AFS and DYC control-oriented vehicle lateral dynamics with multi-uncertainties is developed.The uncertain vehicle lateral dynamics system is augmented with dynamic error, and then the resulting robust feedback controller is finally designed, which ensures the corresponding closed-loop system is asymptotically stable with a quadratic H? performance.Simulation results show that the proposed controller can effectively preserve vehicle yaw stability even when the vehicle undergoes extreme double-lane change maneuvers under high longitudinal velocity. (4)In order to improve vehicle roll stability, the nominal value of vehicle yaw rate is corrected according to the defined roll stability index that is comprised of vehicle load parameter, vehicle roll angle and critical lateral acceleration. Roll stability control-oriented vehicle roll dynamics with uncertainties is developed.The control saturation is also considered due to the physical limitations of actuators, active roll robust controller considering control saturation is designed with Lyapunov theory under unified framework of anti-saturation H? control, the feasibility conditions are derived from Finsler recursive theorem so that the closed-loop system is asymptotically stable and possesses H? level. Simulations show active roll robust controller has lateral stability margin and can avoid vehicle instability caused by the vehicle large roll posture. (5)To demonstrate the effectiveness of proposed estimation algorithm and robust control strategy, road experiments are carried out on distributed drive electric vehicles experimental platform.All road experiments were conducted under low speed due to safety concerns.J-turning and serpentine turning are tested to assess estimation algorithm,and half circle and two long-time continuous intense steering tests are implemented to evaluate robust control strategy.Experiments results verify the effectiveness and the feasibility of developed estimation algorithm and robust control strategy.
学术讨论
主办单位时间地点报告人报告主题
东南大学机械工程学院 2014.11.19 机械楼第一会议室 金贤建 Improving Vehicle Handling Stability Performance via Integrated Control of Active Front Steering and Suspension Systems
东南大学机械工程学院 2015.4.22 机械楼第一会议室 金贤建 分布式驱动电动汽车的平方根容积卡尔曼滤波状态观测
东南大学机械工程学院 2017.3.8 机械楼南高厅 金贤建 Advanced Robust Control For Lateral Stability of Four-Wheel-Independent-Drive Electric Vehicles with DYC
东南大学机械工程学院 2014.11.12 机械楼南高厅 殷国栋教授 轻量化、电动化、智能化汽车的技术发展
东南大学机械工程学院 2015.6.18 机械楼南高厅 Prof. Haiping Du Fuzzy Model Based Vehicle Sideslip Angle Estimation and Lateral Dynamics Control
东南大学机械工程学院 2014.5.6 机械楼第一会议室 金贤建 分布式驱动电动汽车底盘动力学控制研究进展
东南大学机械工程学院 2014.10.24 机械楼南高厅 倪中华教授 微纳医疗器械设计与制造
东南大学机械工程学院 2017.3.13 机械楼南高厅 Prof.Jingang Yi Estimation, Sensing and Control of Tire/Road Interactions
     
学术会议
会议名称时间地点本人报告本人报告题目
2015年机械工程全国博士生学术论坛 2015.4.11 芜湖 Lateral Stability Region Conservativeness Estimation and Torque Distribution For FWIA Electric Vehicle Steering
2015年中国汽车工程学会年会 2015.10.17 上海
2017年机械工程全国博士生学术论坛 2017.05.12 芜湖 Coordinated Braking Control For In-Wheel-Motor-Driven Electric Vehicles with Regenerative and Anti lock Braking System Based on Control Allocation
     
代表作
论文名称
Gain-scheduled Vehicle Handling Stability Control via Integration of Active Front Steering and Suspe
Gain-scheduled Robust Control for Lateral Stability of Four-Wheel-Independent-Drive Electric Vehicle
Robust Guaranteed Cost State-delayed Control of Yaw Stability for Four-Wheel-Independent-Drive Elect
 
答辩委员会组成信息
姓名职称导师类别工作单位是否主席备注
苏小平 正高 教授 博导 南京工业大学
鲁植雄 正高 教授 博导 南京农业大学
陈南 正高 教授 博导 东南大学
孙蓓蓓 正高 教授 博导 东南大学
张建润 正高 教授 博导 东南大学
      
答辩秘书信息
姓名职称工作单位备注
张宁 其他 讲师 东南大学