智能汽车横向运动控制要求转向系统能够及时精确地输出转向角跟踪道路曲率。但目前智能汽车横向运动控制普遍以前轮转向角作为控制目标，忽略了转向系统操纵车辆的中间过程，此种作法除不符合车辆结构实际外，还会降低车辆跟踪道路曲率精度。论文以伺服电机自动转向系统为研究对象，通过建立转向系统动力学等效模型，分析前轮-主销转向特点，优化转向传动机构结构参数，提出转向分层控制算法，控制伺服电机自动转向系统实现智能汽车路径跟踪。
针对转向系统动力学建模不考虑转向梯形几何运动导致转向系统动力学模型精度降低的问题，分析伺服电机自动转向系统传动机构部件运动状态，建立伺服电机自动转向系统动力学等效模型。根据伺服电机自动转向系统物理结构等效出系统的刚度-阻尼-质量结构。对转向传动机构杆系进行几何计算，推导出传动比函数，利用传动比函数计算出前轮转向角与广义回正力矩。采用拉格朗日方程，结合传动比函数，推导出伺服电机自动转向系统动力学方程。Adams/View仿真结果表明：该动力学等效模型能够揭示转向系统非线性传动特性，能够以单自由度分别输出左、右前轮转向角。
忽略车轮定位参数以前轮绕主销转角代替转向角，将导致计算出的转向角不精确，影响转向传动机构的优化精度。针对此问题，通过分析前轮-主销的空间运动关系，构建出前轮转向角计算模型。通过建立局部坐标系与全局坐标系，计算出前轮-主销定位参数投影坐标与轮心绕主销的运动轨迹。采用平移与旋转矩阵，将轮心运动轨迹变换并投影到水平面，从而利用向量夹角公式计算出前轮绕主销转角与转向角间的函数关系。Adams/Car仿真结果表明：主销参数变化不大的情况下，前轮绕主销转角与转向角间的轮-销传动比为定值，通过此传动比可计算出较为精确的转向角。
将转向传动机构当作平面机构优化会导致优化后机构输出的转向角与目标转向角仍具有较大误差。针对此问题，结合转向梯形主销与当量转向梯形间的空间投影关系，对伺服电机自动转系统传动机构进行参数优化。以当量转向梯形推导出转向特征方程作为参数优化的对象。通过分析主销轴线所在的空间四棱锥与转向梯形平面的投影关系确定出优化参数。计算约束条件，利用主销参数、阿克曼率修正阿克曼方程作为目标函数。设计加权均方差作为评价函数，设计分段函数作为适应度函数，采用遗传算法对转向特征方程进行参数优化。优化结果的误差分析表明：主销参数对转向传动机构结构参数与目标函数的计算、转向特征方程的优化均有较大影响，考虑主销参数、主销与转向梯形间的投影关系可提高转向传动机构的精度。
忽略转向系统以转向角作为控制目标进行车辆路径跟踪控制，不符合车辆实际结构，也会降低车辆路径跟踪精度。针对此问题，耦合转向系统与车辆模型，模拟驾驶员操纵转向系统的行为，提出伺服电机自动转向系统转向分层控制算法。通过建立车辆预测模型、添加约束条件、优化求解目标函数，建立上层MPC控制器，模拟驾驶员观察与判断车-路关系，输出期望前轮转向角。利用转向回正力矩耦合车辆模型与转向系统模型，利用车-路误差模型与理想转向角模型，建立转向系统下层拟人控器，模拟驾驶员操纵与微调转向盘的行为，输出实际转向角度跟踪理想转向角度。Simulink与CarSim联合仿真结果表明：该控制算法在不同车速与道路曲率条件下能够控制伺服电机自动转向系统跟踪理想转向角。
为验证所设计转向分层控制算法的有效性与精确性，开展伺服电机自动转向系统台架试验。采用频率响应法，对伺服电机自动转向系统进行参数辨识，获取系统阻尼比、无阻尼自然频率；通过阶跃响应试验与速度控制试验验证伺服电机自动转向系统动力学等效模型的正确性与精确性；分别在 20 km/h、50 km/h、80 km/h车速条件下，开展转向分层控制算法对定曲率与变曲率路径理想转向角的跟踪试验，验证伺服电机自动转向系统动力学等效模型的精确性和转向分层控制算法的有效性。

The lateral motion control of intelligent vehicles requires the steering system to output steering angles accurately and timely to track road curvature. However, the current common practice in lateral motion control of intelligent vehicles is to use the front wheel steering angle as the control target, ignoring the intermediate process of vehicle manipulation by the steering system. This approach not only does not conform to the actual vehicle structure but also reduces the accuracy of vehicle tracking road curvature. This dissertation takes the automatic steering system of servo motors as the research object. By establishing a dynamic equivalent model of the steering system, analyzing the steering characteristics of the front wheel and kingpin, optimizing the structural parameters of the steering transmission mechanism, and proposing a steering hierarchical control algorithm, the automatic steering system of servo motors is controlled to achieve path tracking for intelligent vehicles.
To address the issue of reduced accuracy in steering system dynamics models due to the neglect of the geometric movement of the steering trapezoid, the motion states of the transmission mechanism components is analyzed and the equivalent dynamics model for the servo motor automatic steering system is established. Based on the physical structure of the servo motor automatic steering system, the stiffness-damping-mass structure of the system is equivalent. The geometric calculation of the steering transmission mechanism rods are carried out, and the transmission ratio function is derived. The transmission ratio function is used to calculate the front wheel steering angle and the generalized aligning torque. Using Lagrange's equation and combining with the transmission ratio function, the dynamic equation of the servo motor automatic steering system is derived. Adams/View simulation shows that this dynamic equivalent model can reveal the nonlinear transmission characteristics of the steering system, and can output left and right front wheel steering angles with a single degree of freedom.
Ignoring the wheel alignment parameters and replacing the steering angle with the angle of the front wheel rotating around the kingpin will lead to inaccurate calculation of the steering angle, affecting the optimization accuracy of the steering transmission mechanism. To address this issue, by analyzing the spatial motion relationship between the front wheel and the kingpin, a calculation model for the front wheel steering angle is constructed. By establishing a local coordinate system and a global coordinate system, the projection coordinates of the positioning parameters of the front wheel and the kingpin are calculated, and the motion trajectory of the wheel center around the kingpin is calculated. Using translation and rotation matrices, the motion trajectory of the wheel center is transformed and projected onto a horizontal plane, so that the functional relationship between the rotation angle of the front wheel around the kingpin and the steering angle can be calculated using the vector angle formula. Adams/Car simulation results show that under the condition of small changes in the kingpin parameters, the wheel-to-kingpin transmission ratio between the rotation angle of the front wheel around the kingpin and the steering angle is a constant value, which can be used to calculate a more accurate steering angle.
Treating the steering transmission mechanism as a planar mechanism for optimization can result in errors between the optimized steering angle output and the target steering angle. To address this issue, parameter optimization of the servo motor automatic steering system transmission mechanism is conducted by considering the spatial projection relationship between the kingpin and the equivalent steering trapezoid. The steering characteristic equation derived from the equivalent steering trapezoid is used as the object of parameter optimization. The optimization parameters are determined by analyzing the projection relationship between the space pyramid where the kingpin axis is located and the steering trapezoid plane. The calculation constraints are analyzed, and the Ackermann equation is modified using the kingpin parameters and Ackermann rate as the objective function. The weighted mean square error is designed as the evaluation function, and the piecewise function is designed as the fitness function. The genetic algorithm is used to optimize the parameters of the steering characteristic equation. The error analysis of the optimization results shows that the kingpin parameters have a significant impact on the calculation of structural parameters and objective functions of the steering transmission mechanism, as well as on the optimization of the steering characteristic equation. Considering the projection relationship between the kingpin parameters and the steering trapezoid can improve the accuracy of the steering transmission mechanism.
Ignoring the steering system but using steering angle as the control target for vehicle path tracking control does not align with the actual vehicle structure and can also reduce the accuracy of vehicle path tracking. To address this issue, a steering system hierarchical control algorithm for servo motor automatic steering systems is proposed by coupling the steering system with the vehicle model and simulating the driver's steering system manipulation behavior. The control algorithm integrates the steering system with the vehicle model, simulates the driver's actions in manipulating the steering system. By establishing a vehicle prediction model, adding constraints, optimizing the objective function, and establishing an upper-level MPC controller, the control algorithm simulates the driver's observation and judgment of the relationship between the vehicle and the road, and outputs the desired front wheel steering angle.The generalized aligning torquee is used to couple the vehicle model and the steering system model, and the vehicle-road error model and the ideal steering angle model are used to establish a lower-level human-like controller for the steering system. This controller simulates the driver's actions in manipulating and fine-tuning the steering wheel, and outputs the actual steering angle to track the ideal steering angle. Simulink and CarSim co-simulation show that this control algorithm can control the servo motor automatic steering system to track the ideal steering angle under different vehicle speeds and road curvature conditions.
To verify the effectiveness and accuracy of the steering hierarchical control algorithm, a bench test of the servo motor automatic steering system is conducted. Using frequency response method, the parameters of the servo motor automatic steering system are identified to obtain the system damping ratio and undamped natural frequency. The correctness and accuracy of the dynamic equivalent model of the servo motor automatic steering system are verified through step response test and speed control test. The tracking test of the ideal steering angle for constant curvature and variable curvature paths is conducted at vehicle speeds of 20 km/h, 50 km/h, and 80 km/h, respectively, to verify the accuracy of the dynamic equivalent model of the servo motor automatic steering system and the effectiveness of the steering hierarchical control algorithm.

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