Enhance Vehicle Handling Research Articles

Modelling and experimental validation of an adaptive interconnected suspension with adjustable roll stiffness (AIS-ARS)

Vehicle suspensions play a critical role in improving vehicle stability and ride quality, especially in heavy vehicles that usually have high centre-of-gravity and carry tons of cargo. Interconnected suspension systems, in which the suspension struts are connected through hydraulic hoses and flow control devices, have great potential to enhance vehicle handling stability and attenuate vibrations. This study introduces an adaptive interconnected suspension with adjustable roll stiffness (AIS-ARS) to address the shortcomings of existing designs. It not only eliminates the conventional anti-roll bars but also enables adjustment of roll stiffness depending on the driving and vehicle load conditions. The AIS-ARS system uses a unique design that avoids using expensive electro-proportional flow control valves, which has been a significant barrier to widespread implementation. Instead, the system utilises a cost-effective control strategy that uses only two solenoid valves to achieve adaptive damping. The mathematical modelling of the AIS-ARS is also straightforward, requiring less computational power and making it more practical for real-time implementations. Overall, the AIS-ARS system represents a significant advancement in the design of interconnected suspension systems, offering a more cost-effective, practical, and versatile solution. The above features are validated through laboratory experiments and co-simulation between MATLAB/Simulink and ADAMS/Car.

Design and optimization of two-stage controller for three-phase multi-converter/multi-machine electric vehicle

Abstract Electric vehicles (EVs) cut greenhouse gas emissions and our use of non-renewable resources, making them more attractive. EVs have lower fuel and maintenance expenses than internal combustion engine automobiles. This study proposes a multi-converter/Multi‒Machine system with two induction motors (IM) that drive a pure EV’s rear wheels. EV two-stage controllers using a simple Adaline neural network (NN) regulate Field-Oriented regulate of a three-phase IM. To control IM speed, the first controller level is a hybrid proportional–integral (PI) with a robust integral sign of error (RISE) controller. Injection torque is controlled by PI‒adaline NN in the second controller step. The simple Adaline NN improves two-stage controller performance. The Multi-Verse Optimization algorithm found the ideal RISE parameter to improve EV drive system performance. A plug-in EV’s linear speed is controlled by the Electronic Differential Controller (EDC). It uses the driver’s reference speed and steering angle to set each driving wheel’s reference speed. EDC adjusts wheel speeds to enhance traction and stability during cornering, accelerating, and decelerating. Utilizing this information, the EDC can effectively distribute power and torque to the wheels, thereby enhancing vehicle handling and overall performance. Three distinct road scenarios and the designated driving route topology have been used to act and demonstrate the resistive forces that affected the EV while it was traveling down the road. By using Matlab (Simulink), EV’s roadworthiness and efficiency will be evaluated.

Electric vehicle powertrain and fuzzy controller optimization using a planar dynamics simulation based on a real-world driving cycle

The four-wheel independent-drive electric vehicle (FWID-EV) stands out among the electrically-propelled vehicles due to its higher efficiency. This EV configuration faces an energy management challenge, needing a controller to define the best power split among the motors, decreasing the energy consumption while keeping the EV performance. Aiming to overcome this challenge, this paper presents a fuzzy logic control (FLC) strategy to perform the power split among the electric motors to improve vehicle energy efficiency and dynamic performance under real driving conditions. The implemented controller is developed hierarchically, ensuring the speed follows a driving cycle and acting as an electronic differential to correct the vehicle trajectory along the path. Multi-objective optimization is presented using a particle swarm algorithm (MOPSO) to minimize the mass of the electrical components (motors and battery) and extend the driving range throu gh the maximization of the battery state of charge (SoC). Moreover, the optimization process also aims to enhance vehicle handling by minimizing the driver steering input during the cycle. The best trade-off solution was able to reach a 124.2 km drive range with a 235.8 kg battery (387.8 V and 91.2 Ah), presenting improved handling performance with 78.5% decrease in the driver steering action.

DESIGN AND ASSESSMENT OF A SPEED-BASED INTEGRATED ACTIVE VEHICLE CONTROLLER FOR LATERAL STABILITY

An integrated active vehicle control system implementing fuzzy-logic control (FLC) is introduced. The system integrates three commercially- available active vehicle control systems, namely, Active Front Steering (AFS), Electronic Stability Control (ESC) and Torque Vectoring System (TVS) aiming at enhancing vehicle handling and cornering stability and rollover prevention. Two different vehicle models were constructed to simulate the dynamic behavior of the system with and without the proposed integration controller, namely, a 14-DOF vehicle dynamic model with nonlinear tire characteristics and a 2DOF bicycle reference model. Last model was utilized to generate controller’s reference values of vehicle’s yaw rate and body side slip angle at a given forward speed and driver’s steering input. Simulation was carried out in the MATLAB/SIMULINK software environment. The effectiveness of the system was investigated applying five different standard cornering test maneuvers at different vehicle forward speeds of 10, 20 and 30m/s. Simulated test maneuvers are: step, J-turn, single lane change (SLC), sine with dwell, (SWD) and fishhook.Results reveal that, for stability enhancement, AFS is most effective at low vehicle speeds with declining efficacy as speed goes up. Both ESC and TVS have been found to be equally effective at moderate to high speeds. In conclusion, an integrated chassis control (ICC) strategy has been proposed that improves vehicle handling and cornering performance across the entire operating range of speed using a forward-speed-based stability criterion to allocate stability control authority and ensure smooth transition of control between the three AFS, ESC, and TVS systems.

Adaptive yaw stability control by coordination of active steering and braking with an optimized lower‐level controller

SummaryIn this article, an integrated multiinput multioutput model reference adaptive control algorithm is presented based on active front steering and effective direct yaw moment distribution as an advanced driver assistance system. Vehicle parameter uncertainties in mass and tire‐road friction coefficient are considered through adaptation laws at the upper level in the control structure. The efficient distribution of yaw moment on the rear wheels is performed via a constrained optimization at the lower control level. Control commands are executed by additive steering angle on front wheels and brake torque applied on one of the rear wheels. Simulation results for different lateral maneuvers are employed for the evaluation of the proposed adaptive control method. The performance of the integrated control algorithm to enhance vehicle handling and stability is shown on various road conditions.

Design of a central feedforward control of torque vectoring and rear-wheel steering to beneficially use tyre information

ABSTRACT This paper presents the design of a central feedforward control for the two chassis control systems rear-wheel steering (RWS) and torque vectoring (TV) which have related areas of intervention in lateral dynamics. A control strategy is presented in order to follow desired target values consisting of yaw acceleration and sideslip angle velocity. Central attention is given to the use of additional tyre information with the aim of enhancing vehicle handling and stability. With the knowledge of the mounted tyre type, an adaption law for the desired target values is derived. Although the focus is based on the usage of new tyre information, this modelling approach basically has the potential to reduce the need for coordination among the two systems RWS and TV, exploiting the synergies between both of them. Starting from an extended single-track model an exact Input–output linearisation method is used to design the feedforward control. This is followed by a proof of stability for the external and the internal dynamics of the controller. For the subsequent investigation, in a preliminary step, real-world in vehicle tests are carried out under varying tyre types with a wide spreading of characteristics. This serves as a basis to identify the most important tyre parameters for the controller and to derive the target goals. Finally, the controller is implemented in a 14-DOF non-linear entire vehicle model in Matlab/Simulink, that serves for simulations with a virtual vehicle plant. The performance of the presented feedforward control is assessed by specified objective criteria for steady-state and transient open-loop manoeuvres in lateral dynamics. These criteria are used to investigate the effectiveness of the control design with the aim to achieve the defined target motion. In addition to that, the manoeuvre results also serve to evaluate the control effort, involved in the coordinated cooperation of both systems.

Simultaneous estimation of tire side-slip angle and lateral tire force for vehicle lateral stability control

Knowledge of tire side-slip angle and lateral tire force is crucial to vehicle lateral stability control which can enhance vehicle handling and passenger safety. However, due to high costs of sensors and limitations to sensor technologies, ordinary automobiles cannot measure the tire side-slip angle and lateral tire force directly during vehicle operation. Therefore, the accurate, affordable monitoring of lateral vehicle motion is essential. This paper presents a unified observation algorithm to simultaneously estimate the tire side-slip angle and lateral tire force of all four wheels. Firstly, an adaptive-sliding-mode observer (ASMO) is utilized to estimate the lateral tire force of each wheel. Secondly, the tire side-slip angle of each wheel can be estimated by an adaptive compensation algorithm (ACA). Simulations and real car experiments are used to validate the effectiveness of the proposed approach, and extended kalman filter (EKF) is used to compare with our proposed algorithm. Results show that the designed observer can effectively estimate tire side-slip angles and lateral tire forces of all four wheels, and its performance is better than EKF.

Usage of the Cornering Stiffness for an Adaptive Rear Wheel Steering Feedforward Control

This paper presents the usage of additional tire information in the form of cornering stiffness to enhance vehicle handling and stability with an adaptive rear-wheel steering control (RWS). The influence of varying cornering stiffness on driving behavior is discussed in advance with a single-track model. On the basis of an enhanced single-track model, a RWS feedforward control is presented with a provided tuning parameter adapting the desired rear axle cornering stiffness for the vehicle. In the following, this paper proposes an adaption law that is derived in order to enhance handling performance and safety of a vehicle, taking into account conflicting goals. Finally, simulation results and driving experiments with the adaptive RWS feedforward control are evaluated in both steady-state and transient conditions. In order to examine the full potential of the approach, the controller is adapted to a wide spreading of the cornering stiffness. Therefore, identified cornering stiffnesses of winter-, summer- and ultra-high performance tires are used as a basis for the adaption.

Integrated control of active steering and braking systems with tyre forces and cornering stiffness estimation

A model-based integrated controller for active steering and active braking systems is proposed to enhance vehicle handling and stability. A hierarchical scheme is adopted, including vehicle layer based on model predictive control (MPC), actuator layer, and observer layer. The MPC controller adopts a predictive model with the lateral force of front axle and yaw moment as inputs, which leaves the nonlinearity and coupling of tyre forces to be solved by the tyre force allocation algorithm in actuator layer, leading to more precise control action. In order to maintain satisfactory control performance with respect to the variation of tyre character, a dual extended Kalman filter (DEKF) is designed in the observer layer to estimate tyre forces and cornering stiffness. The observed results are used to reduce the mismatch of the reference models in vehicle layer and actuator layer. The effectiveness of the proposed controller is demonstrated by simulations in CarSim environment.

An integrated algorithm for vehicle stability improvement with the coordination of direct yaw moment and four-wheel steering control

This paper presents an integrated algorithm for enhancing vehicle stability with the coordination of four-wheel steering and direct yaw moment control based on a hierarchical control structure. At the upper level of the integrated control system, the desired four-wheel steering angles and yaw moment are derived using a sliding mode control technique; at the lower level, the control inputs are optimised and implemented using a pseudo-inverse method. A 2 degrees of freedom (DOF) vehicle model is generated to design the integrated control algorithm, and an 8-DOF non-linear vehicle model is developed for numerical simulations. The algorithm is evaluated using a hardware-in-the-loop real-time simulation system (HILS) with the physical implementation of active four-wheel steering and differential braking. It is demonstrated that the proposed algorithm can enhance vehicle handling and stability under different operating conditions.

Estimation of vehicle sideslip angle and individual tyre-road forces based on tyre friction circle concept

The real-time information of vehicle sideslip angle and tyre-road forces of individual wheels can help advanced vehicle chassis control systems to enhance vehicle handling, stability and safety. But in practice, these states are difficult to measure directly for technical and economic reasons. In order to estimate these states, this paper proposes an observer based on Extended Kalman Filter (EKF) by using a 7-DOF vehicle model. According to the Dugoff's tyre model, the lateral force can be expressed by a function of the longitudinal force with the knowledge of tyre work condition. Based on this concept, the reference vehicle model is modified to identify the lateral forces of each braked wheel without the online information of vertical load and tyre-road friction coefficient. The simulation results indicate that the longitudinal and lateral forces of each wheel can be well estimated under combined cornering and braking condition.

Adaptive optimal control for integrated active front steering and direct yaw moment based on approximate dynamic programming

In this paper, a novel adaptive optimal control algorithm based on approximate dynamic programming (ADP) approach is proposed for integrated active front steering (AFS) and direct yaw moment control (DYC). The corrective yaw moment and active steering angle are generated online without knowing system dynamics, which is realised by using a neural network (NN) identifier to identify the unknown system dynamics and a critic NN to calculate the optimal control action, respectively. Control commands are executed via active steering angle on front wheels and proper brake torque distribution on the effective wheels. Computer simulations under three different driving manoeuvres, i.e., lane change manoeuvre, step steer manoeuvre and sine with dwell manoeuvre, are carried out to evaluate the proposed control method. Simulation results show that the proposed ADP-based control method demonstrates improved tracking performance in terms of enhancing vehicle handling and stability performance when encountering the varying longitudinal velocity, the uncertain cornering stiffness and the different road/tyre friction coefficients. Model-free and self-adaptive properties of the proposed method provide a new solution to vehicle stability controller design instead of the commonly used model-based methods.

Adaptive optimal control for integrated active front steering and direct yaw moment based on approximate dynamic programming

In this paper, a novel adaptive optimal control algorithm based on approximate dynamic programming (ADP) approach is proposed for integrated active front steering (AFS) and direct yaw moment control (DYC). The corrective yaw moment and active steering angle are generated online without knowing system dynamics, which is realised by using a neural network (NN) identifier to identify the unknown system dynamics and a critic NN to calculate the optimal control action, respectively. Control commands are executed via active steering angle on front wheels and proper brake torque distribution on the effective wheels. Computer simulations under three different driving manoeuvres, i.e., lane change manoeuvre, step steer manoeuvre and sine with dwell manoeuvre, are carried out to evaluate the proposed control method. Simulation results show that the proposed ADP-based control method demonstrates improved tracking performance in terms of enhancing vehicle handling and stability performance when encountering the varying longitudinal velocity, the uncertain cornering stiffness and the different road/tyre friction coefficients. Model-free and self-adaptive properties of the proposed method provide a new solution to vehicle stability controller design instead of the commonly used model-based methods.

Robust gain-scheduling energy-to-peak control of vehicle lateral dynamics stabilisation

In this paper, we investigate the vehicle lateral dynamics stabilisation problem to enhance vehicle handling by considering time-varying longitudinal velocity. The longitudinal velocity is described by a polytope with finite vertices and a novel technique is proposed to reduce the number of vertices. Since the tyre dynamics is nonlinear, the cornering stiffness is represented via the norm-bounded uncertainty. Concerning the time-varying velocity and the nonlinear tyre model, a linear parameter-varying vehicle model is obtained. As the velocity and the states are measurable, a gain-scheduling state-feedback controller is introduced. In the lateral control, the sideslip angle is required to be as small as possible and the yaw rate is constrained to a certain level. Thus, the control objective is to minimise the sideslip angle while the yaw rate is under a prescribed level or constrain both the sideslip angle and the yaw rate to prescribed levels. To consider the transient response of the closed-loop system, the -stability is also employed in the energy-to-peak control. The optimal controller can be obtained by solving a set of linear matrix inequalities. A nonlinear vehicle model is utilised to illustrate the design procedure and the effectiveness of the proposed design method. Finally, simulations and comparisons are carried out to show the significant advantage of the designed controller. Compared to the open-loop system, the closed-loop system with the designed controller can achieve much smaller sideslip angle and the yaw rate is closer to the desired yaw rate from a reference model. Therefore, the vehicle safety and the handling are both improved in our simulation cases.

Comparison of Static and Dynamic Control Allocation Techniques for Integrated Vehicle Control

AbstractComparison of static and dynamic control allocation techniques for nonlinear constrained optimal distribution of tire forces in a vehicle control system is presented. The total body forces and moments, obtained from a high level controller, are distributed among tire forces, which are constrained to nonlinear constraint of saturation, through two approaches. For the static control allocation technique the interior-point method is employed to perform the nonlinear constrained optimization problem. Also, by the dynamic control allocation technique a dynamic update law is derived for desired forces of each tire. Through simulation results efficiency of two approaches in enhancing vehicle handling and stability is evaluated and the results are compared.

Estimation of Tire Slip Angle and Friction Limits Using Steering Torque

Knowledge of the vehicle's lateral handling limits is important for vehicle control systems which aim to enhance vehicle handling and passenger safety. This paper presents a model-based estimation method that utilizes pneumatic trail information in steering torque to identify a vehicle's lateral handling limits, which are defined by the tire slip angle and peak lateral force limits. This method uses measurements available on many current production vehicles. Most importantly, it takes advantage of the early friction information encoded in the tire pneumatic trail. Pneumatic trail decreases as a function of the tire parameters even in the linear handling region, enabling early detection of the limits before they are reached. Experimental results on an independent front steering steer-by-wire research vehicle demonstrate the observer's ability to provide accurate real-time estimates of tire slip angle up to the limits of handling. Testing conditions include maneuvers performed on dry, flat paved road, as well as on lower-friction, dry gravel.

Lateral load transfer and normal forces estimation for vehicle safety: experimental test

Knowledge of vehicle dynamics data is important for vehicle control systems that aim to enhance vehicle handling and passenger safety. This study introduces observers that estimate lateral load transfer and wheel–ground contact normal forces, commonly known as vertical forces. The proposed method is based on the dynamic response of a vehicle instrumented with cheap and currently available standard sensors. The estimation process is separated into three blocks: the first block serves to identify the vehicle’s mass, the second block contains a linear observer whose main role is to estimate the roll angle and the one-side lateral transfer load, while in the third block we compare linear and nonlinear models for the estimation of four wheel vertical forces. The different observers are based on a prediction/estimation filter. The performance of this concept is tested and compared with real experimental data acquired using the INRETS-MA (Institut National de Recherche sur les Transports et leur Sécurité – Département Mécanismes d’Accidents) Laboratory car. Experimental results demonstrate the ability of this approach to provide accurate estimation, thus showing its potential as a practical low-cost solution for calculating normal forces.

Gain-scheduled integrated active steering and differential control for vehicle handling improvement

This paper presents a gain-scheduled active steering control and active differential design method to preserve vehicle stability in extreme handling situations. A new formulation of the bicycle model in which tyre slip angles, longitudinal slips and vehicle forward speed appear as varying vehicle parameters is introduced. Such a model happens to be useful in the design of vehicle dynamics controllers scheduled by vehicle parameters: after having expressed the parametric bicycle model in the parametric descriptor form, gain-scheduled active steering and differential controllers are designed to improve vehicle handling at ‘large’ driver-commanded steering angles. Simulations reveal the efficiency of the selected modelling and controller design methodology in enhancing vehicle handling capacity during cornering on roads with varying adhesion coefficient and under variable speed operation.

Integrated control of suspension and front steering to enhance vehicle handling

Integration of vehicle chassis control system has gained increasing attention since it can improve the vehicle safety and performance through effective coordination of individual control systems. This paper presents the development of an integrated control system of active front steering and normal force control using fuzzy reasoning to enhance the vehicle-handling performance. Individual control systems were first developed, and then their performances were compared with that of the integrated system. The simulation results indicate that the integrated chassis control scheme utilizing the steering and suspension controllers has proven to be more effective in attaining the desired performance that would not be attained individually.

2105 左右独立インホイールモータとステアバイワイヤの統合制御による操縦安定性向上(操縦分析・制御,OS3 交通・物流システムのダイナミクスと制御,一般講演)

2105 左右独立インホイールモータとステアバイワイヤの統合制御による操縦安定性向上(操縦分析・制御,OS3 交通・物流システムのダイナミクスと制御,一般講演)