Parallel model based fault detection algorithm for electronic parking brake system

This paper describes a parallel model-based fault detection algorithm for an electronic parking brake (EPB) system, which consists of an electronic control unit with built-in current sensor and braking force sensor. For the EPB system to supply sufficient parking force to a vehicle, the parking force sensor is of utmost importance. If a fault occurs in this sensor, sufficient parking force may not be supplied, thereby seriously threatening the safety of the vehicle. Thus, a fault detection method is required for the parking force sensor of the EPB system to improve the safety of vehicles. For this purpose, a highly reliable fault detection method is needed to detect abnormal fault signals, which cannot be detected by the existing on-line sensor monitoring fault detection methods. This paper proposes a novel parallel model-based fault detection algorithm for the EPB system, which compares the physical sensor data with the mathematical model, the fuzzy model, and the neural network model at the same time. In order to reduce false alarms, the magnitude of thresholds and the operation counts are changed adaptively. When the proposed parallel model-based fault detection algorithm detects severe failures of the force sensor, it warns the driver in advance to prevent accidents due to the failures. The proposed algorithm is verified by hardware-in-theloop simulations in various situations.     

线控转向系统转角反步控制算法研究

为实现商用车线控转向,设计一套新的线控转向系统架构及其转角跟踪控制算法。新的线控转向系统采用丝杠螺母结构中的丝杠直接控制纵拉杆,螺母通过带轮机构被电机驱动。对线控转向系统结构进行运动学分析,推导转向系统可变传动比,采用前轮转角为状态变量,建立线控转向系统二阶动力学模型。基于转角跟踪目标,采用反步控制算法,设计线控转向系统转角跟踪控制器,通过反馈系统线性化处理系统参数不确定和环境干扰问题,实现准确的目标转角跟踪,并建立李雅普诺夫函数,证明了采用反步控制的线控转向系统是渐进稳定的。搭建采用“丝杠螺母+带轮机构”架构的线控转向实车底盘测试台架,选取蛇形和混合工况进行控制算法验证。研究结果表明：与滑模控制算法的测试结果对比可知,反步控制算法绝对平均跟踪误差值降低了71.88%~79.57%,跟踪误差标准偏差值降低了71.32%~78.50%;线控转向系统反步控制转角跟踪算法能够减少系统收敛到原点的时间,抑制系统的抖振,提高车辆线控转向系统转角跟踪的操纵灵活性。     

Gain-scheduled EGR control algorithm for light-duty diesel engines with static-gain parameter modeling

This paper presents a model-based gain scheduling algorithm of a PI-based EGR controller for light-duty diesel engines. In order to capture nonlinear characteristic of the EGR system, we have proposed a new scheduling variable to illustrate the static-gain of the plant model as a linear function. The proposed scheduling variable is composed of the air-tofuel ratio of the exhaust gas and the pressure ratio between the exhaust and intake manifolds. Using the scheduling variable, a static-gain model achieved 0.94 of the R-squared value with 810 of steady-state measurements which include key engine operating conditions. Based on the model of the static-gain parameter, the gains of the PI controller are decided by Skogestad internal model control (SIMC) tuning rule in real-time. Through various scenarios of engine experiments, the proposed gain scheduling algorithm represented that the PI gains were successfully adapted according to the changes of the engine operating conditions.     

Model-Based Integrated Control of Engine and CVT to Minimize Fuel Use

In this study, a model-based integrated control method for engines and continuous variable transmissions (CVTs) is developed. CVT refers to a type of transmission which allows an engine to be operated independently with respect to the vehicle speed, with the engine torque and CVT gear ratio controlled in an integrated manner. In the proposed integrated control scheme, engine operating points which minimize the rate of instantaneous fuel consumption are calculated, and the engine target torque and target gear ratio are determined in an integrated manner based on the results of the calculations. Unlike the previous map-based control method, the method introduced in this study does not require an engine torque map or a CVT ratio map for tuning, and the engine torque and CVT ratio are controlled to minimize the amount of fuel used while satisfying the level of acceleration demand from the driver. The control scheme is based on the powertrain model, and the CVT response lag and transmission loss are also considered in the integrated control processes. The algorithm is simulated with various driving cycles, with the simulation results showing that the fuel economy performance of the vehicle system is improved with the newly suggested engine-CVT integrated control algorithm.     

Literature review and fundamental approaches for vehicle and tire state estimation*

ABSTRACT

Most modern day automotive chassis control systems employ a feedback control structure. Therefore, real-time estimates of the vehicle dynamic states and tire-road contact parameters are invaluable for enhancing the performance of vehicle control systems, such as anti-lock brake system (ABS) and electronic stability program (ESP). Today's production vehicles are equipped with onboard sensors (e.g. a 3-axis accelerometer, 3-axis gyroscope, steering wheel angle sensor, and wheel speed sensors), which when used in conjunction with certain model-based or kinematics-based observers can be used to identify relevant tire and vehicle states for optimal control of comfort, stability and handling. Vehicle state estimation is becoming ever more relevant with the increased sophistication of chassis control systems. This paper presents a comprehensive overview of the state-of-the-art in the field of vehicle and tire state estimation. It is expected to serve as a resource for researchers interested in developing vehicle state estimation algorithms for usage in advanced vehicle control and safety systems.     

Design of a rollover index-based vehicle stability control scheme

This paper presents a rollover index (RI)-based vehicle stability control (VSC) scheme. A rollover index, which indicates an impending rollover, is developed by a roll dynamics phase plane analysis. A model-based roll estimator is designed to estimate the roll angle and roll rate of the vehicle body with lateral acceleration, yaw rate, steering angle and vehicle velocity measurements. The rollover index is computed using an estimated roll angle, estimated roll rate, measured lateral acceleration and time-to-wheel lift. A differential braking control law is designed using a direct yaw control method. The VSC threshold is determined from the rollover index. The effectiveness of the RI, the performance of the estimator and the control scheme are investigated via simulations using a validated vehicle simulator. It is shown that the proposed RI can be a good measure of the danger of rollover and the proposed RI-based VSC scheme can reduce the risk of a rollover.     

Identification of nonlinear systems using modified particle swarm optimisation: a hydraulic suspension system

This paper presents a novel modified particle swarm optimisation (MPSO) algorithm to identify nonlinear systems. The case of study is a hydraulic suspension system with a complicated nonlinear model. One of the main goals of system identification is to design a model-based controller such as a nonlinear controller using the feedback linearisation. Once the model is identified, the found parameters may be used to design or tune the controller. We introduce a novel mutation mechanism to enhance the global search ability and increase the convergence speed. The MPSO is used to find the optimum values of parameters by minimising the fitness function. The performance of MPSO is compared with genetic algorithm and alternative particle swarm optimisation algorithms in parameter identification. The presented comparisons confirm the superiority of MPSO algorithm in terms of the convergence speed and the accuracy without the premature convergence problem. Furthermore, MPSO is improved to detect any changes of system parameters, which can be used for designing an adaptive controller. Simulation results show the success of the proposed algorithm in tracking time-varying parameters.     

基于扰动观测的客车ESC自适应神经网络滑模控制

为了提高客车电子稳定性控制系统(ESC)的控制精度,针对实际车辆系统建模中存在各种非线性扰动项以及传统滑模控制(Sliding Mode Control,SMC)中抖振较大的问题,提出一种自适应神经网络滑模控制算法.基于2自由度车辆模型,首先设计一个二阶滑模(Second-order Sliding Mode,SOSM...     

电动液压助力转向系统控制算法研究与实现

研究了电动液压助力转向控制系统中转向盘角速度、车速和电机转速之间非线性关系的控制算法,并依据实际控制系统参数,得到该控制系统中车速、电机转速及转向角速度三者的非线性关系,利用仿真软件实现了控制系统所需要的助力曲线。通过在AMESIM中仿真对比表明,运用该算法能够得到较理想的助力曲线,验证了该算法在电动液压助力转向系统中应用的可行性。通过台架试验表明,该系统助力效果明显,控制算法中参数变换对控制系统的影响与实际控制系统控制效果相吻合。     

Study of strategy for model-based cooperative control of EGR and VGT in a diesel engine

There is a mutual influence between the effects of controlling exhaust gas recirculation (EGR) and a variable geometry turbocharger (VGT). This paper presents an approach through the application of a control system CAD program and rapid prototyping tools to improve transient operating states by referring to a model-based exhaust recirculation and variable geometry turbocharger control algorithm. The operation model for estimating the state conditions of EGR and a VGT was built on the controller. Simulation and experimental results demonstrating the effectiveness of optimized transient control are also described.     

Model-based fault detection and isolation in automotive yaw moment control system

This paper presents a model-based fault detection and isolation technique for automotive yaw moment control system. For this purpose, a novel fault detection and isolation algorithm for a class of actuator-plant systems is proposed. Compared with the existing fault detection and isolation techniques that can only isolate a target fault or require multiple observers to isolate multiple faults, a unique strength of the proposed algorithm is its ability to isolate faults at the component level solely based on the residuals generated by a single observer. The validity of the proposed algorithm, applied to automotive yaw moment control system, is investigated via a simulation study based on a realistic vehicle dynamics model. The results suggest that the proposed algorithm can isolate the component subject to fault while effectively handling two perennial nuisances: sensitivity to disturbances and false alarms due to uncertainties.     

Integrated control of ground vehicles dynamics via advanced terminal sliding mode control

An integrated vehicle dynamics control (IVDC) algorithm, developed for improving vehicle handling and stability under critical lateral motions, is discussed in this paper. The IVDC system utilises integral and nonsingular fast terminal sliding mode (NFTSM) control strategies and coordinates active front steering (AFS) and direct yaw moment control (DYC) systems. When the vehicle is in the normal driving situation, the AFS system provides handling enhancement. If the vehicle reaches its handling limit, both AFS and DYC are then integrated to ensure the vehicle stability. The major contribution of this paper is in improving the transient response of the vehicle yaw rate and sideslip angle tracking controllers by implementing advanced types of sliding mode strategies, namely integral terminal sliding mode and NFTSM, in the IVDC system. Simulation results demonstrate that the developed control algorithm for the IVDC system not only has strong robustness against uncertainties but also improves the transient response of the control system.     

A vehicle stability control strategy with adaptive neural network sliding mode theory based on system uncertainty approximation

Modelling uncertainty, parameter variation and unknown external disturbance are the major concerns in the development of an advanced controller for vehicle stability at the limits of handling. Sliding mode control (SMC) method has proved to be robust against parameter variation and unknown external disturbance with satisfactory tracking performance. But modelling uncertainty, such as errors caused in model simplification, is inevitable in model-based controller design, resulting in lowered control quality. The adaptive radial basis function network (ARBFN) can effectively improve the control performance against large system uncertainty by learning to approximate arbitrary nonlinear functions and ensure the global asymptotic stability of the closed-loop system. In this paper, a novel vehicle dynamics stability control strategy is proposed using the adaptive radial basis function network sliding mode control (ARBFN-SMC) to learn system uncertainty and eliminate its adverse effects. This strategy adopts a hierarchical control structure which consists of reference model layer, yaw moment control layer, braking torque allocation layer and executive layer. Co-simulation using MATLAB/Simulink and AMESim is conducted on a verified 15-DOF nonlinear vehicle system model with the integrated-electro-hydraulic brake system (I-EHB) actuator in a Sine With Dwell manoeuvre. The simulation results show that ARBFN-SMC scheme exhibits superior stability and tracking performance in different running conditions compared with SMC scheme.     

Design and evaluation of sideslip angle observer for vehicle stability control

This paper presents a method for estimating the vehicle side slip angle, which is considered as a significant signal in determining the vehicle stability region in vehicle stability control systems. The proposed method combines the model-based method and kinematics-based method. Side forces of the front and rear axles are provided as a weighted sum of directly calculated values from a lateral acceleration sensor and a yaw rate sensor and from a tire model according to the nonlinear factor, which is defined to identify the degree of nonlinearity of the vehicle state. Then, the side forces are fed to the extended Kalman filter, which is designed based on the single-track vehicle model associated with a tire model. The cornering stiffness identifier is introduced to compensate for tire force nonlinearities. A fuzzy-logic procedure is implemented to determine the nonlinear factor from the input variables: yaw rate deviation from the reference value and lateral acceleration. The proposed observer is compared with a model-based method and kinematics-based method. An 8 DOF vehicle model and Dugoff tire model are employed to simulate the vehicle state in MATLAB/SIMULINK. The simulation results shows that the proposed method is more accurate than the model-based method and kinematics-based method when the vehicle is subjected to severe maneuvers under different road conditions.     

基于模型控制的未来柴油机开发（英文）

Heavy duty diesel vehicles compliant with current Euro VI/EPA13 emission limits employ aftertreatment systems based on DOC/DPF technology for soot and particulate matter reduction and SCR catalysts with urea dosing for NO x reduction. Traditionally, the majority of the control systems used for urea dosing are map based. However, increasing system complexity combined with real-world performance requirements are a strong motivation to switch to a model-based control approach. Firstly, this article describes a model-based design approach for aftertreatment control development. Focus is on urea dosing control for Euro VI level SCR systems. To achieve the legal emissions limits, including in-service conformity over the vehicle lifetime, advanced model-based control strategies enable maximal NO x conversion in combination with minimum ammonia slip, while ensuring robustness against real-life disturbances. Simulation and experimental results of the control system are presented, which demonstrate the performance and robustness properties. Following this model-based approach, a concept study is performed to explore aftertreatment and control technologies to achieve ultra-low NO x emissions as will be imposed by regulatory bodies in the near future. It is shown that aftertreatment concepts with Passive NO x Adsorber and SCR on DPF are most promising. To optimize overall engine-aftertreatment performance, the modelbased control approach is extended towards Integrated Emission Management(IEM). Based on the actual system state, this supervisory controller minimizes operating costs at each instant in time under all operating conditions. This is key for costoptimal and robust performance.     

数控伞钻控制系统开发及Unity3D的应用

为提高钻爆法竖井施工的安全性,实现伞钻自动化施工,开发伞钻控制系统。首先介绍伞钻功能、结构等被控对象背景,之后分别从控制系统硬件、运动控制算法及人机界面软件、Unity3D功能应用等3方面进行描述。搭载该控制系统的伞钻装置进行多次钻孔试验,结果证明： 该系统整体功能、效率、精度达到设计目标,能实现凿岩过程的自动化,提高施工的安全性;Unity3D的应用可方便主司机获取伞钻各动臂位姿信息,也能从软件上降低各动臂机械干涉概率。     

基于ReliefF-RBF的路面不平度识别算法研究

路面不平度对道路车辆行驶安全性及车辆动力学响应具有重要影响。通过将路面不平度识别与先进悬架控制结合,有望能进一步提升乘员舒适性和车辆的操纵稳定性。现有基于数据驱动的路面分类方法难以高效处理时变参数与车速,现有基于模型的路面识别算法需要已知精确车辆模型,在实际应用中面临车辆物理参数难以获得的问题。提出一种融合模型和数据驱动的路面分类算法,采用基于模型的方法反算等效路面轮廓,结合数据预处理方法,对车辆响应和反算等效路面轮廓数据进行滤波;对等效路面轮廓和响应信息进行时域频域特征计算,采用ReliefF算法进行关键特征提取,构建基于径向基函数神经网络的路面分类器,进行路面分级识别;通过仿真试验和实车试验验证了不同车辆参数和车速下所提出的算法鲁棒性。     

Optimal preview game theory approach to vehicle stability controller design

Dynamic game theory brings together different features that are keys to many situations in control design: optimisation behaviour, the presence of multiple agents/players, enduring consequences of decisions and robustness with respect to variability in the environment, etc. In the presented methodology, vehicle stability is represented by a cooperative dynamic/difference game such that its two agents (players), namely the driver and the direct yaw controller (DYC), are working together to provide more stability to the vehicle system. While the driver provides the steering wheel control, the DYC control algorithm is obtained by the Nash game theory to ensure optimal performance as well as robustness to disturbances. The common two-degrees-of-freedom vehicle-handling performance model is put into discrete form to develop the game equations of motion. To evaluate the developed control algorithm, CarSim with its built-in nonlinear vehicle model along with the Pacejka tire model is used. The control algorithm is evaluated for a lane change manoeuvre, and the optimal set of steering angle and corrective yaw moment is calculated and fed to the test vehicle. Simulation results show that the optimal preview control algorithm can significantly reduce lateral velocity, yaw rate, and roll angle, which all contribute to enhancing vehicle stability.     

Adaptive feedforward control of a steer-by-wire system by online parameter estimator

The tracking control of the steer-by-wire (SBW) system to achevie desired steering motion is the core issue for the design of algorithm. Most of model-based tracking control assumed the constant parameters without the consideration of dynamic characteristics. The external disturbances and model nonlinearities can bring uncertainties of the system parameters. To reduce the influence of parameter uncertainties, an online estimator by output error identification method is proposed to estimate the dynamic parameters of a SBW system. Meanwhile, the parameter gradient projection method is applied to eliminate the parameter drift, while a full order state observer is developed to weaken the effects of noise disturbance during the parameter identification. Since the sensitivity of parameter uncertainties for the feedforward control, the online estimator is incorporated into the control model and improve the controlled robustness. The proposed adaptive feedforward controller is conducted by the real-time experiments to show the tracking performance.     

Robust yaw stability control for electric vehicles based on active front steering control through a steer-by-wire system

A robust yaw stability control design based on active front steering control is proposed for in-wheel-motored electric vehicles with a Steer-by-Wire (SbW) system. The proposed control system consists of an inner-loop controller (referred to in this paper as the steering angle-disturbance observer (SA-DOB), which rejects an input steering disturbance by feeding a compensation steering angle) and an outer-loop tracking controller (i.e., a PI-type tracking controller) to achieve control performance and stability. Because the model uncertainties, which include unmodeled high frequency dynamics and parameter variations, occur in a wide range of driving situations, a robust control design method is applied to the control system to simultaneously guarantee robust stability and robust performance of the control system. The proposed control algorithm was implemented in a CaSim model, which was designed to describe actual in-wheel-motored electric vehicles. The control performances of the proposed yaw stability control system are verified through computer simulations and experimental results using an experimental electric vehicle.