High-speed optimal steering of a tractor–semitrailer

A high-speed optimal trailer steering controller for a tractor–semitrailer is discussed. A linear model of a tractor–semitrailer with steered trailer axles is described, and an optimal trailer steering controller is introduced. A path-following controller is derived to minimise the path-tracking error in steady-state manoeuvres using active trailer steering. A roll stability controller is introduced by adding the lateral acceleration of trailer centre of gravity as another objective in the steering controller, so as to improve roll stability in transient manoeuvres. A strategy to switch between these two control modes is demonstrated. Simulation results show that the steering controller can ensure good path tracking of articulated vehicles in steady-state manoeuvres and improve roll stability significantly in transient manoeuvres, while maintaining the path-tracking deviation within an acceptable range. Tests with an experimental tractor–semitrailer equipped with a high-bandwidth active steering system validate the controller design and simulation results. The roll stability controller reduces the measured rearward amplification by 27%.     

A lateral driver model for vehicle–driver closed-loop simulation at the limits of handling

This paper presents a lateral driver model for vehicle–driver closed-loop simulation at the limits of handling. An appropriate driver model can be used to evaluate the performance of vehicle chassis control systems via computer simulations before vehicle tests which incurs expenses especially at the limits of handling. The driver model consists of two parts. The first part is an upper-level controller employing force-based approach to reduce the number of unknown vehicle parameters. The feedforward part of the upper controller has been designed by using the centre of percussion. The feedback part aims to minimise ‘tangential error’, defined as the sum of body slip angle and yaw error, to match vehicle direction and road heading angle. The part is designed to regenerate an appropriate skid motion similar to that of a professional driver at the limits. The second part is a lower-level controller which converts the desired front lateral force to steering wheel angle. The lower-level controller also consists of feedforward and feedback parts. A two-degree-of-freedom bicycle model-based feedforward part provides nominal steering wheel angle, and the feedback part aims to eliminate unmodelled error. The performance of the lateral driver model has been investigated via computer simulations. It has been shown that the steering behaviours of the proposed driver model are quite close to those of a professional driver at the limits. Compared with the previously developed lateral driver models, the proposed lateral driver model shows good tracking performance at the limits of handling.     

具有先进保护功能的新型IGBT门极驱动器集成电路

论述了IGBT门极驱动器设计新方案,它具有先进的保护功能,如元件采用双电平开通以减小峰值电流,采用双电平关断以限制过电压,以及防止出现桥臂贯通的有源密勒箝位.此外还介绍一种包括双电平关断驱动器和有源密勒箝位功能的新电路,并对所述功能的试验及结果进行阐述,重点介绍双电平关断驱动器的中间电平对IGBT过电压的影响.     

司机控制器机械寿命试验台的设计

司机控制器机械寿命试验台采用步进电机作为驱动元件,可近似模拟司机控制器在不同操作频率、不同往复角度等工况下的运行情况,并将实验数据实时记录下来。文章详细介绍了该试验台的总体方案和电气控制部分。     

Model predictive driving simulator motion cueing algorithm with actuator-based constraints

The simulator motion cueing problem has been considered extensively in the literature; approaches based on linear filtering and optimal control have been presented and shown to perform reasonably well. More recently, model predictive control (MPC) has been considered as a variant of the optimal control approach; MPC is perhaps an obvious candidate for motion cueing due to its ability to deal with constraints, in this case the platform workspace boundary. This paper presents an MPC-based cueing algorithm that, unlike other algorithms, uses the actuator positions and velocities as the constraints. The result is a cueing algorithm that can make better use of the platform workspace whilst ensuring that its bounds are never exceeded. The algorithm is shown to perform well against the classical cueing algorithm and an algorithm previously proposed by the authors, both in simulation and in tests with human drivers.     

地铁车辆基地司机登车平台优化设计

文章通过对地铁车辆基地司机登车平台布置型式及特征研究分析,提出以下观点:①司机登车平台台阶应朝向通道位置;②司机登车平台应安装在司机室司机视角的左侧车门位置;③全自动驾驶地铁,司机登车平台应采取对地绝缘措施;④为更好的适应停车位置的变化和地面施工误差,司机登车平台台面高度应能连续微调。     

基于中国人体驾乘姿态的汽车人机空间布置研究

合理的人机空间布置对汽车的舒适性与安全性至关重要,人体驾乘姿态是汽车人机空间布置的依据。文章设计试验,扫描得到500样本分别在8辆车中的驾乘姿态数据,对数据进行统计分析,建立驾驶员座椅适宜线方程与中国人体2D模板,基于标杆车进行验证,结果显示,方程及模板精度较高,符合中国人体驾乘特征。该研究为汽车人机空间布置提供理论依据,为研发适合中国人驾乘的车辆提供支撑,对建立中国汽车人机设计体系具有重要意义。     

Modelling minimum-time manoeuvering with global optimisation of local receding horizon control

In this paper, we explore the notion that a human driver uses a receding horizon model predictive control (MPC) scheme for minimum-time manoeuvering. However, MPC is an inherently sub-optimal control scheme because not all future information is incorporated into its finite preview horizon. In many practical applications, this sub-optimality is tolerated as the solution is sufficiently close to optimal. However, it is known that professional drivers have the ability to learn driving circuits and exploit its features to minimise their global manoeuvering time. In this paper, we will model their process with a cascaded optimisation structure. Therein, the inner-loop features a local MPC scheme tasked with finding the control inputs that achieve a blended objective of minimising time and maximising velocity in each preview horizon/distance. The outer loop of this cascaded structure computes the best set of weights for the two components of the local objectives in order to minimise the global manoeuvering time. The proposed cascaded optimisation and control approach is compared against a straight-forward fixed-cost time optimal MPC applied to minimum-time manoeuvering over two well-known race courses. The paper also includes an extended literature review and details of the computational formulation of the model approach.     

基于生理信号的多任务下驾驶员认知负荷的评定

为探索驾驶员精神状态与生理信号之间的关系,建立基于生理信号的认知负荷评价方法,在驾驶模拟器中设置了驾驶任务和语音交互任务这一典型的双任务模拟驾驶工况,记录实验过程中驾驶员的主观评分及心电、皮电和呼吸等生理信号,并运用统计方法分析生理参数在整个实验过程中的动态变化规律。结果表明,相对于单一驾驶任务,双任务工况下驾驶员感受的主观压力随着任务难度的增加而上升;心率变异性功率谱密度、皮电水平和呼吸频率等生理指标与驾驶员的认知状态具有较强的关联性,因而可以有效区分不同认知负荷的两种状态。