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An Analytical Redundancy-Based Fault Detection and Isolation Algorithm for a Road-Wheel Control Subsystem in a Steer-By-Wire System

机译:线控转向系统中基于冗余度的基于分析的故障检测和隔离算法

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This paper presents a novel observer-based analytical redundancy for a steer-by-wire (SBW) system. An analytical redundancy methodology was utilized to reduce the total number of redundant road-wheel angle (RWA) sensors in a triply redundant RWA-based SBW system while maintaining a high level of reliability. A full-state observer was designed using the combined model of the vehicle and SBW system to estimate the vehicle-body sideslip angle. The steering angle was then estimated from the observed and measured states of the vehicle (body sideslip angle and yaw rate) as well as the current input to the SBW electric motor(s). A fault detection and isolation (FDI) algorithm was developed using a majority voting scheme, which was then used to detect faulty sensor(s) to maintain safe drivability. The proposed analytical redundancy-based FDI algorithms and the linearized vehicle model were modeled in SIMULINK. Simulation results show that the proposed analytical redundancy-based FDI algorithm provides the same level of fault tolerance as in an SBW system with full hardware redundancy against single-point failures.
机译:本文提出了一种新颖的基于观测器的线控转向(SBW)系统分析冗余。利用分析冗余方法来减少基于三重冗余RWA的SBW系统中的冗余车轮角(RWA)传感器的总数,同时保持较高的可靠性。使用车辆和SBW系统的组合模型设计了一个全状态观测器,以估计车身侧滑角。然后根据车辆的观察和测量状态(车身侧滑角和横摆率)以及输入到SBW电动机的电流估算转向角。使用多数表决方案开发了一种故障检测和隔离(FDI)算法,然后将该算法用于检测故障传感器以保持安全的驾驶性能。在SIMULINK中对所提出的基于分析冗余的FDI算法和线性化车辆模型进行了建模。仿真结果表明,所提出的基于分析冗余的FDI算法可提供与SBW系统相同的容错能力,而SBW系统具有针对单点故障的完整硬件冗余。

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