Vehicle dynamic stability improvements through gain-scheduled steering and braking control

This paper is concerned with the synthesis of a robust gain-scheduled ?_∞ MIMO vehicle dynamic stability controller (VDSC) involving both steering and rear braking actuators. This VDSC aims at improving automotive vehicle yaw stability and lateral performances. The aim of this work is to provide a methodology to synthesise such a controller while taking into account the braking actuator limitations and use the steering actuator only if it is necessary. These objectives are treated in an original way by the synthesis of a parameter-dependent controller built in the LPV framework and by the solution of an LMI problem. The proposed solution is coupled with a local ABS strategy to guarantee slip stability and make the solution complete. Nonlinear time and frequency domain simulations on a complex full vehicle model (which has been validated on a real car), subject to critical driving situations, show the efficiency and robustness of the proposed solution.     

Vehicle velocity estimation using effective inertia for an in-wheel electric vehicle

In this study, a vehicle velocity estimation algorithm for an in-wheel electric vehicle is proposed. This algorithm estimates the vehicle velocity using the concept of effective inertia, which is based on the motor torque, the angular velocity of each wheel and vehicle acceleration. Effective inertia is a virtual mass that changes according to the state of a vehicle, such as acceleration, deceleration, turning or driving on a low friction road. The performance of the proposed vehicle velocity estimation algorithm was verified in various conditions that included straight driving, circle driving and low friction road driving using the in-wheel electric vehicle that was equipped with an in-wheel system in each of its rear wheels.     

Vehicle stability control system for enhancing steerabilty,lateral stability,and roll stability

The Vehicle stability control system is an active safety system designed to prevent accidents from occurring and to stabilize dynamic maneuvers of a vehicle by generating an artificial yaw moment using differential brakes. In this paper, in order to enhance vehicle steerability, lateral stability, and roll stability, each reference yaw rate is designed and combined into a target yaw rate depending on the driving situation. A yaw rate controller is designed to track the target yaw rate based on sliding mode control theory. To generate the total yaw moment required from the proposed yaw rate controller, each brake pressure is properly distributed with effective control wheel decision. Estimators are developed to identify the roll angle and body sideslip angle of a vehicle based on the simplified roll dynamics model and parameter adaptation approach. The performance of the proposed vehicle stability control system and estimation algorithms is verified with simulation results and experimental results.     

Vehicle stability control using direct virtual sensors

The paper investigates the use of a direct virtual sensor (DVS) to replace a physical sensor in a vehicle stability control system. A yaw control system is considered and the proposed solution can be particularly useful when a fault of the yaw rate physical sensor occurs. A DVS is a stable linear filter derived directly from input–output data, collected in a preliminary experiment. In this work, it is shown that, by using data collected in a closed-loop fashion, better DVS accuracy can be obtained with a reduced number of measured variables. Moreover, the robust stability of the closed-loop system employing a DVS is studied. The effectiveness of the presented results is shown through numerical simulations of harsh manoeuvres, performed using a detailed model of a vehicle equipped with an active front steering device.     

Vehicle longitudinal velocity estimation during the braking process using unknown input Kalman filter

In this paper, vehicle longitudinal velocity during the braking process is estimated by measuring the wheels speed. Here, a new algorithm based on the unknown input Kalman filter is developed to estimate the vehicle longitudinal velocity with a minimum mean square error and without using the value of braking torque in the estimation procedure. The stability and convergence of the filter are analysed and proved. Effectiveness of the method is shown by designing a real experiment and comparing the estimation result with actual longitudinal velocity computing from a three-axis accelerometer output.     

Vehicle dynamic estimation with road bank angle consideration for rollover detection: theoretical and experimental studies

This article describes a method of vehicle dynamics estimation for impending rollover detection. This method is evaluated via a professional vehicle dynamics software and then through experimental results using a real test vehicle equipped with an inertial measurement unit. The vehicle dynamic states are estimated in the presence of the road bank angle (as a disturbance in the vehicle model) using a robust observer. The estimated roll angle and roll rate are used to compute the rollover index which is based on the prediction of the lateral load transfer. In order to anticipate the rollover detection, a new method is proposed in order to compute the time-to-rollover using the load transfer ratio. The used nonlinear model is deduced from the vehicle lateral dynamics and is represented by a Takagi–Sugeno (TS) fuzzy model. This representation is used in order to take into account the nonlinearities of lateral cornering forces. The proposed TS observer is designed with unmeasurable premise variables in order to consider the non-availability of the slip angles measurement. Simulation results show that the proposed observer and rollover detection method exhibit good efficiency.     

Vehicle yaw stability control using active limited-slip differential via model predictive control methods

In this paper, the problem of vehicle yaw control using an active limited-slip differential (ALSD) applied on the rear axle is addressed. The controller objective is to minimise yaw-rate and body slip-angle errors, with respect to target values. A novel model predictive controller is designed, using a linear parameter-varying (LPV) vehicle model, which takes into account the ALSD dynamics and its constraints. The controller is simulated using a 10DOF Matlab/Simulink simulation model and a CarSim model. These simulations exemplify the controller yaw-rate and slip-angle tracking performances, under challenging manoeuvres and road conditions. The model predictive controller performances surpass those of a reference sliding mode controller, and can narrow the loss of performances due to the ALSD's inability to transfer torque regardless of driving conditions.     

Self-tuning control algorithm design for vehicle adaptive cruise control system through real-time estimation of vehicle parameters and road grade

The main purpose of this paper is to design a self-tuning control algorithm for an adaptive cruise control (ACC) system that can adapt its behaviour to variations of vehicle dynamics and uncertain road grade. To this aim, short-time linear quadratic form (STLQF) estimation technique is developed so as to track simultaneously the trend of the time-varying parameters of vehicle longitudinal dynamics with a small delay. These parameters are vehicle mass, road grade and aerodynamic drag-area coefficient. Next, the values of estimated parameters are used to tune the throttle and brake control inputs and to regulate the throttle/brake switching logic that governs the throttle and brake switching. The performance of the designed STLQF-based self-tuning control (STLQF-STC) algorithm for ACC system is compared with the conventional method based on fixed control structure regarding the speed/distance tracking control modes. Simulation results show that the proposed control algorithm improves the performance of throttle and brake controllers, providing more comfort while travelling, enhancing driving safety and giving a satisfactory performance in the presence of different payloads and road grade variations.     

Vehicle dynamic control of a passenger car applying flexible body model

Modern software tools have enhanced modelling, analysis and simulation capabilities pertaining to control of dynamic systems. In this regard, in this paper a full vehicle model with flexible body is exposed by using MSC. ADAMS and MSC. NASTRAN. Indeed, one of the most significant vehicle dynamic controls is directional stability control. In this case, the vehicle dynamic control system (VDC) is used to improving the vehicle lateral and yaw motions in critical manoeuvres. In this paper, for design the VDC system, an optimal control strategy has been used for tracking the intended path with optimal energy. For better performance of VDC system, an anti-lock brake system (ABS) is designed as a lower layer of the control system for maintaining the tyre longitudinal slip in proper value. The performances of the controller on rigid and flexible models are illustrated, and the results show the differences between the control efforts for these models, which are related to the differences of dynamic behaviours of rigid and flexible vehicle dynamic models.     

Lateral stability control of dynamic steering for dual motor drive high speed tracked vehicle

In this paper, the torque and power required by dual motors for electric tracked vehicle during dynamic steering maneuvers with different steering radiuses are analyzed. A steering coupling drive system composed of a new type of center steering motor, two Electromagnetic (EM) clutches, two planetary gear couplers, and two propulsion motors is proposed for the dual motors drive high speed electric tracked vehicle (2MHETV), which aims to improve its lateral stability. An average torque direct distribution control strategy based on steering coupling and an optimization-distribution-based close-loop control strategy are designed separately to control the driving torque or regenerative braking torque of two propulsion motors for vehicle stability enhancement. Then models of the 2MHETV and the proposed control strategy are established in Recudyn and Matlab/Simulink respectively to evaluate the lateral stability of dynamic steering for the 2MHETV with different steering radiuses on hard pavement.The simulation results show that the lateral stability of the 2MHETV can be significantly improved by the proposed optimization-distribution-based close-loop control strategy based on steering coupling system.     

Vehicle sideslip estimation and compensation for banked road

The sideslip driving status is of fundamental importance to the stability of a vehicle. This paper presents a practical vehicle sideslip driving status estimation method that uses ESP (electronic stability program) sensors. ESP sensors such as wheel speed, lateral acceleration, yaw rate and steering wheel angle sensors are used to determine the sideslip driving status and distinguish a banked road. This estimation algorithm contains front-rear sideslip and banked road detection methods. The proposed sideslip estimation algorithm was designed to use the analytical redundancy of these sensors and Lagrange interpolation methods. The performance and effectiveness of the proposed estimation and compensation algorithm were investigated using vehicle tests. This paper presents the results of two cases that were used for the experimental verification: a curved flat road and banked road.     

The characteristic velocity stability indicator for passenger cars

Driver assistance systems have received increased attention as market demands have pushed for improved automotive safety. These systems are designed to aid the driver by preventing any unstable or unpredictable vehicle behaviour. One global indicator for stability and driving conditions could help to manage the control algorithms and driver warning subroutines. Another problem which could be solved by a precise driving situation indicator is evaluating new vehicles during test drives. After a short introduction to a linear lateral vehicle model, an analytical approach for an online calculation of different driving conditions (i.e., stability, understeering, oversteering, and neutralsteering) is given. A characteristic velocity stability indicator is defined, which allows online computation of the present driving condition. Results are then checked against real measurements of a test vehicle.     

多媒体定时器在汽车操纵稳定性实时测试系统中的应用

基于Visual Basic6．0开发了汽车操纵稳定性实时测试系统．该系统利用Windows多媒体定时器技术实现了对实验数据的实时采集、实时显示。从根本上改变了早期基于DOS开发的测试系统人机交互功能差的缺点,在实际工程中取得了较好的应用效果。     

The characteristic velocity stability indicator for passenger cars

Driver assistance systems have received increased attention as market demands have pushed for improved automotive safety. These systems are designed to aid the driver by preventing any unstable or unpredictable vehicle behaviour. One global indicator for stability and driving conditions could help to manage the control algorithms and driver warning subroutines. Another problem which could be solved by a precise driving situation indicator is evaluating new vehicles during test drives. After a short introduction to a linear lateral vehicle model, an analytical approach for an online calculation of different driving conditions (i.e., stability, understeering, oversteering, and neutralsteering) is given. A characteristic velocity stability indicator is defined, which allows online computation of the present driving condition. Results are then checked against real measurements of a test vehicle.     

Reduction of engine emissions via a real-time engine combustion control with an egr rate estimation model

Vehicle emissions regulations are becoming increasingly severe and remain a principal issue for vehicle manufacturers. Since, WLTP (Worldwide harmonized Light vehicles Test Procedures) and RDE (real driving emission) regulations have been recently introduced, the engine operating conditions have been rapidly changed during the emission tests. Significantly more emissions are emitted during transient operation conditions compared to those at steady state operation conditions. For a diesel engine, combustion control is one of the most effective approaches to reduce engine exhaust emissions, particularly during the transient operation. The concern of this paper is about reducing emissions using a closed loop combustion control system which includes a EGR rate estimation model. The combustion control system calculates the angular position where 50 % of the injected fuel mass is burned (MFB50) using in-cylinder pressure for every cycle. In addition, the fuel injection timing is changed to make current MFB50 follow the target values. The EGR rate can be estimated by using trapped air mass and in-cylinder pressure when the intake valves are closed. When the EGR rate is different from the normal steady conditions, the target of MFB50 and the fuel injection timing are changed. The accuracy of the model is verified through engine tests, as well as the effect of combustion control. The peaks in NO level was decreased during transient conditions after adoption of the EGR model-based closed loop combustion control system.     

Vehicle modeling with nonlinear tires for vehicle stability analysis

The dynamic stability of a vehicle depends on various maneuvering features, such as traction, braking, and cornering. This study presents nonlinear vehicle models for estimating the stability region and simulating the dynamic behavior of a vehicle. Two types of vehicle models were found by considering the degrees of freedom and linearity. A simple model with nonlinear tire dynamics is useful for determining the stability region, while a complex model (a multi-body dynamic model in MSC.ADAMS) is appropriate for carrying out accurate simulations. Actual data for a mid-sized passenger car were used, and the models were validated by comparison with test results.     

Vehicle distance estimation using a mono-camera for FCW/AEB systems

For robust vision-based forward collision warning (FCW) and autonomous emergency braking (AEB) systems, not only reliable detection performance including high detection rate and low false positives but also accurate measurement output of a target vehicle is required. Especially, in order to reduce false alarm or activation of FCW/AEB systems, the systems require the precise measurement output of a target object, such as position, velocity, acceleration, and time-to-collision (TTC). In this study, we developed a measurement estimation algorithm of a target vehicle using a monocular camera. This method estimates two cases of vehicle widths for a target vehicle by using the detected lane information and a pin-hole camera model. After that, the position, velocity, acceleration, and TTC of a target vehicle are estimated by using a Kalman filter for the each estimated vehicle width. To improve robustness, the both estimation results using the detected lane information and the pinhole camera model are fused. This estimation algorithm was evaluated and compared with the state-of-the-art technology. As a result, the proposed measurement output estimation method can improve the performance of the FCW/AEB systems.     

Sideslip angle estimation considering short-duration longitudinal velocity variation

The accurate estimation of sideslip angle is necessary for many vehicle control systems. The detection of sliding and skidding is especially critical in emergency situations. In this paper, a sideslip angle estimation method is proposed that considers severe longitudinal velocity variation over the short period of time during which a vehicle may lose stability due to sliding or spinning. An extended Kalman filter (EKF) based on a kinematic model of a vehicle is used without initialization of the inertial measurement unit to estimate vehicle longitudinal velocity. A dynamic compensation method that compensates for the difference in the locations of the vehicle velocity sensor and the IMU in on-road vehicle tests is proposed. Evaluations with a CarSim™ 27-degree-of-freedom (DOF) model for various vehicle test scenarios and with on-road tests using a real vehicle show that the proposed sideslip angle estimation method can accurately predict sideslip angle, even when vehicle longitudinal velocity changes significantly.     

Full drive-by-wire dynamic control for four-wheel-steer all-wheel-drive vehicles

Most of the controllers introduced for four-wheel-steer (4WS) vehicles are derived with the assumption that the longitudinal speed of the vehicle is constant. However, in real applications, the longitudinal speed varies, and the longitudinal, lateral, and yaw dynamics are coupled. In this paper, the longitudinal dynamics of the vehicle as well as its lateral and yaw motions are controlled simultaneously. This way, the effect of driving/braking forces of the tires on the lateral and yaw motions of the vehicle are automatically included in the control laws. To address the dynamic parameter uncertainty of the vehicle, a chatter-free variable structure controller is introduced. Elimination of chatter is achieved by introducing a dynamically adaptive boundary layer thickness. It is shown via simulations that the proposed control approach performs more robustly than the controllers developed based on dynamic models, in which longitudinal speed is assumed to be constant, and only lateral speed and yaw rate are used as system states. Furthermore, this approach supports all-wheel-drive vehicles. Front-wheel-drive or rear-wheel-drive vehicles are also supported as special cases of an all-wheel-drive vehicle.