Integrated Control of Active Rear Wheel Steering and Direct Yaw Moment Control

An integrated control system of active rear wheel steering (4WS) and direct yaw moment control (DYC) is presented in this paper. Because of the tire nonlinearity that is mainly due to the saturation of cornering forces, vehicle handling performance is improved but limited to a certain extent only by steering control. Direct yaw moment control using braking and/or driving forces is effective not only in linear but also nonlinear ranges of tire friction circle. The proposed control system is a model matching controller which makes the vehicle follow the desired dynamic model by the state feedback of both yaw rate and side slip angle. Various computer simulations are carried out and show that vehicle handling performance is much improved by the integrated control system.     

Integrated Control of Active Rear Wheel Steering and Direct Yaw Moment Control

SUMMARY

An integrated control system of active rear wheel steering (4WS) and direct yaw moment control (DYC) is presented in this paper. Because of the tire nonlinearity that is mainly due to the saturation of cornering forces, vehicle handling performance is improved but limited to a certain extent only by steering control. Direct yaw moment control using braking and/or driving forces is effective not only in linear but also nonlinear ranges of tire friction circle. The proposed control system is a model matching controller which makes the vehicle follow the desired dynamic model by the state feedback of both yaw rate and side slip angle. Various computer simulations are carried out and show that vehicle handling performance is much improved by the integrated control system.     

Direct tire force generation algorithm based on non-iterative nonlinear inverse tire model

The function of vehicle dynamics control system is adjusting the yaw moment, the longitudinal force and lateral force of a vehicle body through several chassis systems, such as brakes, steering and suspension. Individual systems such as ESC, AFS and 4WD can be used to achieve desired performance by controlling actuator variables. However, integrated chassis control systems that have multiple objectives may not simply achieve the desired performance by controlling the actuators directly. Usually those systems determine the required tire forces in an upper level controller and a lower level controller regulates the tire forces through the actuators. The tire force is controlled in a recursive way based on vehicle state measurement, which may not be sufficient for fast response. For immediate force tracking, we introduce a direct tire force generation method that uses a nonlinear inverse tire model, a pseudo-inverse model of vehicle dynamics and the relationship between longitudinal force and brake pressure.     

Lateral handling improvement with dynamic curvature control for an independent rear wheel drive EV

The integrated longitudinal and lateral dynamic motion control is important for four wheel independent drive (4WID) electric vehicles. Under critical driving conditions, direct yaw moment control (DYC) has been proved as effective for vehicle handling stability and maneuverability by implementing optimized torque distribution of each wheel, especially with independent wheel drive electric vehicles. The intended vehicle path upon driver steering input is heavily depending on the instantaneous vehicle speed, body side slip and yaw rate of a vehicle, which can directly affect the steering effort of driver. In this paper, we propose a dynamic curvature controller (DCC) by applying a the dynamic curvature of the path, derived from vehicle dynamic state variables; yaw rate, side slip angle, and speed of a vehicle. The proposed controller, combined with DYC and wheel longitudinal slip control, is to utilize the dynamic curvature as a target control parameter for a feedback, avoiding estimating the vehicle side-slip angle. The effectiveness of the proposed controller, in view of stability and improved handling, has been validated with numerical simulations and a series of experiments during cornering engaging a disturbance torque driven by two rear independent in-wheel motors of a 4WD micro electric vehicle.     

Multi-axle vehicle dynamics stability control algorithm with all independent drive wheel

The stability driving characteristic and the tire wear of 8-axle vehicle with 16-independent driving wheels are discussed in this paper. The lateral stability of 8-axle vehicle can be improved by the direct yaw moment which is generated by the 16 independent driving wheels. The hierarchical controller is designed to determine the required yaw torque and driving force of each wheel. The upper level controller uses feed-forward and feed-backward control theory to obtain the required yaw torque. The fuzzification weight ratio of two control objective is built in the upper level controller to regulate the vehicle yaw and lateral motions. The rule-based yaw moment distribution strategy and the driving force adjustment based on the safety of vehicle are proposed in the lower level controller. The influence of rear steering angle is considered in the distribution of driving force of the wheel. Simulation results of a vehicle double lane change show the stability of 8-axle vehicle under the proposed control algorithm. The wear rate of tire is calculated by the interaction force between the tire and ground. The wear of tire is different from each other for the vehicle with the stability controller or not.     

Integrated fuzzy/optimal vehicle dynamic control

There are basically two methods to control yaw moment which is the most efficient way to improve vehicle stability and handling. The first method is indirect yaw moment control, which works based on control of the lateral tire force through steering angle control. It is mainly known as active steering control (ASC). Nowadays, the most practical approach to steering control is active front steering (AFS). The other method is direct yaw moment control (DYC), in which an unequal distribution of longitudinal tire forces (mainly braking forces) produces a compensating external yaw moment. It is well known that the AFS performance is limited in the non-linear vehicle handling region. On the other hand, in spite of a good performance of DYC in both the linear and non-linear vehicle handling regions, continued DYC activation could lead to uncomfortable driving conditions and an increase in the stopping distance in the case of emergency braking. It is recommended that DYC be used only in high-g critical maneuvers. In this paper, an integrated fuzzy/optimal AFS/DYC controller has been designed. The control system includes five individual optimal LQR control strategies; each one, has been designed for a specific driving condition. The strategies can cover low, medium, and high lateral acceleration maneuvers on high-μ or low-μ roads. A fuzzy blending logic also has been utilized to mange each LQR control strategy contribution level in the final control action. The simulation results show the advantages of the proposed control system over the individual AFS or DYC controllers.     

Handling Capabilities of Vehicles in Emergencies Using Coordinated AFS and ARMC Systems

In this paper, an advanced control technique that can be implemented in hard emergency situations of vehicles is introduced. This technique suggests integration between Active Front Steering (AFS) and Active Roll Moment Control (ARMC) systems in order to enhance the vehicle controllability. For this purpose, the AFS system applies a robust sliding mode controller (SMC) that is designed to influence the steering input of the driver by adding a correction steering angle for maintaining the vehicle yaw rate under control all the time. The AFS system is then called active-correction steering control. The ARMC system is designed to differentiate the front and rear axles' vertical suspension forces in order to alter the vehicle yaw rate and to eliminate the vehicle roll motion as well. Moreover, the operation of the SMC is based on tracking the behavior of a nonlinear 2-wheel model of 2-DOF used as a reference model. The 2-wheel model incorporates real tire characteristics, which can be inferred by the use of trained neural networks. The results clearly demonstrate the enhanced characteristics of the proposed control technique. The SMC with the assistance of the ARMC provides less correction of the steering angle and accordingly reduces the possibility of occurrence of the saturation phenomenon that is likely to take place in the operation of the SMC systems.     

Handling Capabilities of Vehicles in Emergencies Using Coordinated AFS and ARMC Systems

In this paper, an advanced control technique that can be implemented in hard emergency situations of vehicles is introduced. This technique suggests integration between Active Front Steering (AFS) and Active Roll Moment Control (ARMC) systems in order to enhance the vehicle controllability. For this purpose, the AFS system applies a robust sliding mode controller (SMC) that is designed to influence the steering input of the driver by adding a correction steering angle for maintaining the vehicle yaw rate under control all the time. The AFS system is then called active-correction steering control. The ARMC system is designed to differentiate the front and rear axles' vertical suspension forces in order to alter the vehicle yaw rate and to eliminate the vehicle roll motion as well. Moreover, the operation of the SMC is based on tracking the behavior of a nonlinear 2-wheel model of 2-DOF used as a reference model. The 2-wheel model incorporates real tire characteristics, which can be inferred by the use of trained neural networks. The results clearly demonstrate the enhanced characteristics of the proposed control technique. The SMC with the assistance of the ARMC provides less correction of the steering angle and accordingly reduces the possibility of occurrence of the saturation phenomenon that is likely to take place in the operation of the SMC systems.     

Additional 4WS and Driver Interaction

This investigation is based on a complex 4-wheel vehicle model of a passenger car that includes steering system and drive train. The tyre properties are described for all possible combined longitudinal and lateral slip values and for arbitrary friction conditions. The active part is an additional steering system of all 4 wheels, additionally to the driver's steering wheel angle input. Three control levels are used for the driver model that thereby can follow a given trajectory or avoid an obstacle.

The feedback control of the additional 4 wheel steering is based on an observer which can also have adaptive characteristics. Moreover a virtual vehicle model in a feedforward scheme can provide desired steering characteristics.

To get information for critical situations a cornering manoeuvre with sudden u-split conditions is simulated. Further a similar manoeuvre is used to evaluate the reentry in a high friction area from low friction conditions. And finally the performance of the controller is shown in a severe lane change manoeuvre.     

Independent Suspension, Self Steered Axle, and 4WS for Busses

The dynamic behavior of commercial vehicles fitted with differentr types of suspension mechanisms and steering devices is investigated in this paper. Six vehicle models have been constructed: 2WS-SA is a standard two wheel steering bus with solid axles; 2WS-DW is a 2WSA vehicle with independent double wishbone suspension in front and rear axles; SSA-SA is a 2WS system with solid axles, the rear one being mounted on a self steered mechanism; SSA-DW is a vehicle with independent double wishbone suspension in the front axle, and a solid self steered rear axle; 4WS-SA has four wheel steering with solid axles; and 4WS-DW is a 4WS vehicle with independent double wishbone suspension in front and rear axles. The dynamic response of these models has been assessed in terms of lateral acceleration, yaw velocity, tire forces, tire force reserves, and slip angles. The expected advantages of a 4WS system (higher acceleration rates and lower slip angles) will be corroborated but, at the same time, it will be shown that they are obtained at the cost of lower force reserves. Self steered mechanisms produce smaller body slip angles, but it will be shown that they give rise to larger yaw velocity overshootings. The particular independent suspension analyzed does not show significant improvements with respect to the solid axle counterpart.     

Optimum distribution of yaw moment for unified chassis control with limitations on the active front steering angle

This paper describes an optimum distribution method for yaw moment for use with unified chassis control (UCC) with limitations on the active front steering (AFS) angle. Although the UCC has been assumed to have no AFS angle limitation in the literature, a physical limitation exists in real applications. To improve upon the previous method, a new optimum distribution method for yaw moment is proposed that takes this limitation into account. This method derives an optimum longitudinal/lateral force using the Karush-Kuhn-Tucker (KKT) optimality condition, and a simulation is performed to validate the proposed method. The simulation results indicate that the limitation on the AFS angle increases longitudinal braking force and, therefore, reduces the vehicle speed and the side-slip angle.     

Nonlinear PI front and rear steering control in four wheel steering vehicles

Vehicle steering dynamics show resonances, which depend on the longitudinal speed, unstable equilibrium points and limited stability regions depending on the constant steering wheel angle, longitudinal speed and car parameters.

The main contribution of this paper is to show that a combined decentralized proportional active front steering control and proportional-integral active rear steering control from the yaw rate tracking error can assign the eigenvalues of the linearised single track steering dynamics, without lateral speed measurements, using a standard single track car model with nonlinear tire characteristics and a non-linear first-order reference model for the yaw rate dynamics driven by the driver steering wheel input. By choosing a suitable nonlinear reference model it is shown that the responses to driver step inputs tend to zero (or reduced) lateral speed for any value of longitudinal speed: in this case the resulting controlled vehicle static gain from driver input to yaw rate differs from the uncontrolled one at higher speed. The closed loop system shows the advantages of both active front and rear steering control: higher controllability, enlarged bandwidth for the yaw rate dynamics, suppressed resonances, new stable cornering manoeuvres, enlarged stability regions, reduced lateral speed and improved manoeuvrability; in addition comfort is improved since the phase lag between lateral acceleration and yaw rate is reduced.

For the designed control law a robustness analysis is presented with respect to system failures, driver step inputs and critical car parameters such as mass, moment of inertia and front and rear cornering stiffness coefficients. Several simulations are carried out on a higher order experimentally validated nonlinear dynamical model to confirm the analysis and to explore the robustness with respect to unmodelled dynamics.     

Modeling and control of an anti-lock brake and steering system for cooperative control on split-mu surfaces

The brake and steering systems in vehicles are the most effective actuators that directly affect the vehicle dynamics. In general, the brake system affects the longitudinal dynamics and the steering system affects the lateral dynamics; however, their effects are coupled when the vehicle is braking on a non-homogenous surface, such as a split-mu road. The yaw moment compensation of the steering control on a split-mu road is one of the basic functions of integrated or coordinated chassis control systems and has been demonstrated by several chassis suppliers. However, the disturbance yaw moment is generally compensated for using the yaw rate feedback or using wheel brake pressure measurement. Access to the wheel brake pressure through physical sensors is not cost effective; therefore, we modeled the hydraulic brake system to avoid using physical sensors and to estimate the brake pressure. The steering angle controller was designed to mitigate the non-symmetric braking force effect and to stabilize the yaw rate dynamics of the vehicle. An H-infinity design synthesis was used to take the system model and the estimation errors into account, and the designed controller was evaluated using vehicle tests.     

Stability enhancement and fuel economy of the 4-wheel-drive hybrid electric vehicles by optimal tyre force distribution

In this paper, vehicle stability control and fuel economy for a 4-wheel-drive hybrid vehicle are investigated. The integrated controller is designed within three layers. The first layer determines the total yaw moment and total lateral force made by using an optimal controller method to follow the desired dynamic behaviour of a vehicle. The second layer determines optimum tyre force distribution in order to optimise tyre usage and find out how the tyres should share longitudinal and lateral forces to achieve a target vehicle response under the assumption that all four wheels can be independently steered, driven, and braked. In the third layer, the active steering, wheel slip, and electrical motor torque controllers are designed. In the front axle, internal combustion engine (ICE) is coupled to an electric motor (EM). The control strategy has to determine the power distribution between ICE and EM to minimise fuel consumption and allowing the vehicle to be charge sustaining. Finally, simulations performed in MATLAB/SIMULINK environment show that the proposed structure could enhance the vehicle stability and fuel economy in different manoeuvres.     

On the handling performance of a vehicle with different front-to-rear wheel torque distributions

ABSTRACT

The handling characteristic is a classical topic of vehicle dynamics. Usually, vehicle handling is studied by analyzing the understeer coefficient in quasi-steady-state maneuvers. In this paper, experimental tests are performed on an electric vehicle with four independent motors, which is able to reproduce front-wheel-drive, rear-wheel-drive and all-wheel-drive (FWD, RWD and AWD, respectively) architectures. The handling characteristics of each architecture are inferred through classical and new concepts. The study presents a procedure to compute the longitudinal and lateral tire forces, which is based on a first estimate and a subsequent correction of the tire forces that guarantee the equilibrium. A yaw moment analysis is performed to identify the contributions of the longitudinal and lateral forces. The results show a good agreement between the classical and new formulations of the understeer coefficient, and allow to infer a relationship between the understeer coefficient and the yaw moment analysis. The handling characteristics vary with speed and front-to-rear wheel torque distribution. An apparently surprising result arises at low speed: the RWD architecture is the most understeering configuration. This is discussed by analyzing the yaw moment caused by the longitudinal forces of the front tires, which is significant for high values of lateral acceleration and steering angle.     

基于NMPC的智能汽车纵横向综合轨迹跟踪控制

本文中针对大曲率转弯工况下,智能汽车纵横向动力学特性的耦合和动力学约束导致轨迹跟踪精度和稳定性下降的问题,提出一种基于非线性模型预测控制(NMPC)的纵横向综合轨迹跟踪控制方法,通过NMPC和障碍函数法(BM)的有效结合,提高了跟踪精度,改善了行驶稳定性.首先建立四轮驱动-前轮转向智能汽车动力学模型和轨迹跟踪模型,采用...     

Additional 4WS and Driver Interaction

SUMMARY

This investigation is based on a complex 4-wheel vehicle model of a passenger car that includes steering system and drive train. The tyre properties are described for all possible combined longitudinal and lateral slip values and for arbitrary friction conditions. The active part is an additional steering system of all 4 wheels, additionally to the driver's steering wheel angle input. Three control levels are used for the driver model that thereby can follow a given trajectory or avoid an obstacle.

The feedback control of the additional 4 wheel steering is based on an observer which can also have adaptive characteristics. Moreover a virtual vehicle model in a feedforward scheme can provide desired steering characteristics.

To get information for critical situations a cornering manoeuvre with sudden u-split conditions is simulated. Further a similar manoeuvre is used to evaluate the reentry in a high friction area from low friction conditions. And finally the performance of the controller is shown in a severe lane change manoeuvre.     

Crosswind Feedforward Control – A Measure to Improve Vehicle Crosswind Behaviour

SUMMARY

The theory of crosswind feedforward control was explained using the example of a vehicle with active front-wheel steering. Beforehand, the calculation formulas and frequency responses of the transient crosswind force and of the wind yaw moment acting on the vehicle were derived using the example of a simple vehicle fluid model. The influence of the transiency of crosswind disturbance on the dynamic crosswind behaviour of a vehicle was then presented. The results of simulation confirmed the analyses carried out in the frequency domain for feedforward control with front, rear and all-wheel steering. With front-wheel steering, the influence of crosswind on one of the vehicle movement variables (lateral acceleration or yaw rate) could be almost completely compensated by dynamic feedforward control. With rear-wheel steering, it is only possible to compensate directly for the influence on the yawing rate. Due to the setting of the side force in the same direction as the lateral wind force at the start, active rear-wheel steering is not so successful as active front-wheel steering. Nevertheless, the crosswind behaviour of a vehicle can be considerably enhanced by feedforward control with rear-wheel steering. The best crosswind behaviour was obtained with active all-wheel steering: the vehicle hardly responds at all to crosswinds and remains on course despite heavy gusts of wind.     

Selection of Actuator Combination in Integrated Chassis Control Using Taguchi Method

This paper presents a method to select the actuator combination in integrated chassis control using Taguchi method. Electronic stability control (ESC), active front and rear steering (AFS/ARS) are used as an actuator, which is needed to generate a control tire force. After computing the control yaw moment in the upper-level controller, it is distributed into the control tire forces, generated by ESC, AFS and ARS in the lower-level controller. In this paper, the weighted pseudo-inverse control allocation (WPCA) with variable weights is used to determine the control tire forces of each actuator. Taguchi method is adopted for sensitivity analysis on variable weights of WPCA in terms of the control performances such as the maneuverability and the lateral stability. For sensitivity analysis, simulation is performed on a vehicle simulation package, CarSim. From sensitivity analysis, the most effective actuator combination is selected.     

Nonlinear PI front and rear steering control in four wheel steering vehicles

Vehicle steering dynamics show resonances, which depend on the longitudinal speed, unstable equilibrium points and limited stability regions depending on the constant steering wheel angle, longitudinal speed and car parameters.

The main contribution of this paper is to show that a combined decentralized proportional active front steering control and proportional-integral active rear steering control from the yaw rate tracking error can assign the eigenvalues of the linearised single track steering dynamics, without lateral speed measurements, using a standard single track car model with nonlinear tire characteristics and a non-linear first-order reference model for the yaw rate dynamics driven by the driver steering wheel input. By choosing a suitable nonlinear reference model it is shown that the responses to driver step inputs tend to zero (or reduced) lateral speed for any value of longitudinal speed: in this case the resulting controlled vehicle static gain from driver input to yaw rate differs from the uncontrolled one at higher speed. The closed loop system shows the advantages of both active front and rear steering control: higher controllability, enlarged bandwidth for the yaw rate dynamics, suppressed resonances, new stable cornering manoeuvres, enlarged stability regions, reduced lateral speed and improved manoeuvrability; in addition comfort is improved since the phase lag between lateral acceleration and yaw rate is reduced.

For the designed control law a robustness analysis is presented with respect to system failures, driver step inputs and critical car parameters such as mass, moment of inertia and front and rear cornering stiffness coefficients. Several simulations are carried out on a higher order experimentally validated nonlinear dynamical model to confirm the analysis and to explore the robustness with respect to unmodelled dynamics.