Wheel Torque Control Research Articles

Automotive wheel torque control systems

The approaches of foreign specialists to improving electronic control systems for the dynamic state of vehicles (traction, directional stability, rollover resistance) to improve their safe operation are analyzed. The three main components of the Active Transmission Torque Management (ADTM) system are considered: the center clutch, the electronic limited slip differential (ELSD), and the torque vectoring system. The possibilities and limitations of using active torque control systems to ensure vehicle safety are shown. Keywords: electronic control, vehicle dynamics, wheel torque, torque vectoring, active safety. alexey.scherbin@nami.ru

Research on Collaborative Control of Differential Drive Assisted Steering and Active Front Steering for Distributed Drive Electric Vehicles

A collaborative control strategy for distributed drive electric vehicles (DDEVs) focusing on differential drive assisted steering (DDAS) and active front steering (AFS) is proposed to address the issues of sudden torque changes, reduced steering characteristics, and weak collaborative control capabilities caused by the coupling of the AFS and DDAS systems in DDEVs. This paper establishes a coupled dynamic model of the AFS and DDAS systems and, on this basis, designs AFS controllers for yaw velocity feedback control and DDAS controllers for steering wheel torque control, respectively. Additionally, it analyzes the interference factors of the two control systems and develops a collaborative control strategy for DDAS and AFS; this control strategy establishes a corner motor correction module, steering wheel torque correction module, and assistance correction module. Co-simulation is carried out on Matlab/Simulink and the Carsim platform to verify the correctness of the model under typical working conditions; to reduce the sudden change in the steering wheel torque caused by AFS additional angle interventions; to improve the poor steering characteristics caused by DDAS, introducing additional yaw torque; to greatly enhance the collaborative control effect; and to meet the requirements for vehicle handling stability, portability, and safety.

Neural Approximation-Based Adaptive Control Using Reinforced Gain for Steering Wheel Torque Tracking of Electric Power Steering System

In practice, steering wheel torque (SWT) control performance for an electric power steering (EPS) system may degrade owing to various reasons, such as model/parameter uncertainties and unpredictable large external disturbances (e.g., reaction force). Furthermore, the desired SWT suddenly varies and its sign also changes because the direction of the steering wheel angle (SWA) often changes according to the driver. In this article, a neural network (NN) approximation-based adaptive nonlinear control (ANC) using reinforced gain (RG) for an EPS system is proposed to resolve the above-mentioned problems using an SWT model. The proposed control method employs an NN approximator, ANC, and RG. The NN approximator is designed to estimate the unknown complex nonlinear function in EPS modeling. The ANC is designed via backstepping to compensate for parametric uncertainties and external disturbances. Further, the RG is designed as a positive nonlinear function of the error to sufficiently suppress the error according to variations in the desired SWT and external disturbance. The RG increases to suppress the error at a rapid transient response, owing to the sudden change in the sign of the desired SWT and the external disturbance. Thus, a high gain (increased RG) is used only when necessary so that an unnecessarily high gain can be avoided.

Stability Control Modeling and Simulation Strategy for an Electric Vehicle Using Two Separate Wheel Drives

This study of modifying the frame forces of an electric vehicle offers benefits for controlling stability. We used a two-wheeled self-driving electric vehicle in this study. Taking into account important parameters such as vehicle speed, the vehicle's stability criterion is determined based on the torque level and lateral slip angle. It is equipped with a traction control system that integrates its dynamic system with a sporty design. This level of control improves the vehicle's stability and safety. A conventional regulator has been developed and trained to apply motor control to a sophisticated power supply system. The stability of the EVs was controlled by a simulation model. We validated the proposed stability criterion, and the wheel torque control algorithm. Stability control for two-wheeled autonomous vehicles can be developed on the basis of related research. We would like to stress that the controller can be used in a variety of modern electric vehicles because it is so easy to use. An overview of the modeling and simulation results for this system in the MATLAB-Simulink environment will be presented.

Stability Control for Electric Vehicles with Four In-Wheel-Motors Based on Sideslip Angle

Tire longitudinal forces of electrics vehicle with four in-wheel-motors can be adjusted independently. This provides advantages for its stability control. In this paper, an electric vehicle with four in-wheel-motors is taken as the research object. Considering key factors such as vehicle velocity and road adhesion coefficient, the criterion of vehicle stability is studied, based on phase plane of sideslip angle and sideslip-angle rate. To solve the problem that the sideslip angle of vehicles is difficult to measure, an algorithm for estimating the sideslip angle based on extended Kalman filter is designed. The control method for vehicle yaw moment based on sliding-mode control and the distribution method for wheel driving/braking torque are proposed. The distribution method takes the minimum sum of the square for wheel load rate as the optimization objective. Based on Matlab/Simulink and Carsim, a cosimulation model for the stability control of electric vehicles with four in-wheel-motors is built. The accuracy of the proposed stability criterion, the algorithm for estimating the sideslip angle and the wheel torque control method are verified. The relevant research can provide some reference for the development of the stability control for electric vehicles with four in-wheel-motors.

Design and Development of a Novel Independent Wheel Torque Control of 4WD Electric Vehicle

In this paper, a novel hybrid vehicle chassis is designed without assisted steering system and its kinematics model, dynamics model as well as a model of the control system. The existing steering mechanism does not provide enough torque or has a shortage of mechanical strength and control. The proposed design has the capability to solve these problems easily. In the first part of this study, the design and development of the vehicle are introduced. After that, a new 4-wheel-drive (4WD) hybrid vehicle chassis including a vehicle platform, a control device, and self-steering mechanism is designed. Its kinematics and dynamics models are built. Furthermore, to optimize the control model and linkage are added between the front and rear bodies. In addition, the new hybrid vehicle chassis has been tested in actual driving. The reliability and feasibility of the vehicle are evaluated by UG software. The open-loop simulation for validation is performed by MATLAB. Finally, traditional proportion-integration-differentiation (PID) control system of the improved model of vehicle chassis is presented. Therein, the PID feedback control loop was employed to track the reference torque of 4-independent wheels. The results are verified using the real-time vehicle. The proposed design is proved feasibility not only has a small turning radius but also has a high control precision, which ensures the flexibility of the vehicle and can control the direction as well. In addition, the proposed design is best for modern agricultural vehicle and can be implemented in commercial and private vehicles.

An energy-efficient torque-vectoring algorithm for electric vehicles with multiple motors

In electric vehicles with multiple motors, the individual wheel torque control, i.e., the so-called torque-vectoring, significantly enhances the cornering response and active safety. Torque-vectoring can also increase energy efficiency, through the appropriate design of the reference understeer characteristic and the calculation of the wheel torque distribution providing the desired total wheel torque and direct yaw moment. To meet the industrial requirements for real vehicle implementation, the energy-efficiency benefits of torque-vectoring should be achieved via controllers characterised by predictable behaviour, ease of tuning and low computational requirements. This paper discusses a novel energy-efficient torque-vectoring algorithm for an electric vehicle with in-wheel motors, which is based on a set of rules deriving from the combined consideration of: i) the experimentally measured electric powertrain efficiency maps; ii) a set of optimisation results from a non-linear quasi-static vehicle model, including the computation of tyre slip power losses; and iii) drivability requirements for comfortable and safe cornering response. With respect to the same electric vehicle with even wheel torque distribution, the simulation results, based on an experimentally validated vehicle dynamics simulation model, show: a) up to 4% power consumption reduction during straight line operation at constant speed; b) >5% average input power saving in steady-state cornering at lateral accelerations >3.5 m/s2; and c) effective compensation of the yaw rate and sideslip angle oscillations during extreme transient tests.

Unified decision-making and control for highway collision avoidance using active front steer and individual wheel torque control

ABSTRACTCollision avoidance is a crucial function for all ground vehicles, and using integrated chassis systems to support the driver presents a growing opportunity in active safety. With actuators such as in-wheel electric motors, active front steer and individual wheel brake control, there is an opportunity to develop integrated chassis systems that fully support the driver in safety critical situations. Here we consider the scenario of an impending frontal collision with a stationary or slower moving vehicle in the same driving lane. Traditionally, researchers have approached the required collision avoidance manoeuver as a hierarchical scheme, which separates the decision-making, path planning and path tracking. In this context, a key decision is whether to perform straight-line braking, or steer to change lanes, or indeed perform combined braking and steering. This paper approaches the collision avoidance directly from the perspective of constrained dynamic optimisation, using a single optimisation procedure to cover these aspects within a single online optimisation scheme of model predictive control (MPC). While the new approach is demonstrated in the context of a fully autonomous safety system, it is expected that the same approach can incorporate driver inputs as additional constraints, yielding a flexible and coherent driver assistance system.

Energy-Efficient Torque-Vectoring Control of Electric Vehicles With Multiple Drivetrains

The safety benefits of torque-vectoring control of electric vehicles with multiple drivetrains are well known and extensively discussed in the literature. Also, several authors analyze wheel torque control allocation algorithms for reducing the energy consumption while obtaining the wheel torque demand and reference yaw moment specified by the higher layer of a torque-vectoring controller. Based on a set of novel experimental results, this study demonstrates that further significant energy consumption reductions can be achieved through the appropriate tuning of the reference understeer characteristics. The effects of drivetrain power losses and tire slip power losses are discussed for the case of identical drivetrains at the four vehicle corners. Easily implementable yet effective rule-based algorithms are presented for the set-up of the energy-efficient reference yaw rate, feedforward yaw moment and wheel torque distribution of the torque-vectoring controller.

Frequency and time domain characteristics of digital control of electric vehicle in-wheel drives

Abstract In-wheel electric drives are promising as actuators in active safety systems of electric and hybrid vehicles. This new function requires dedicated control algorithms, making it essential to deliver models that reflect better the wheel-torque control dynamics of electric drives. The timing of digital control events, whose importance is stressed in current research, still lacks an analytical description allowing for modeling its influence on control system dynamics. In this paper, authors investigate and compare approaches to the analog and discrete analytical modeling of torque control loop in digitally controlled electric drive. Five different analytical models of stator current torque component control are compared to judge their accuracy in representing drive control dynamics related to the timing of digital control events. The Bode characteristics and stepresponse characteristics of the analytical models are then compared with those of a reference model for three commonly used cases of motor discrete control schemes. Finally, the applicability of the presented models is discussed.

An optimal wheel-torque control on a compliant modular robot for wheel-slip minimization

SUMMARYThis paper discusses the development of an optimal wheel-torque controller for a compliant modular robot. The wheel actuators are the only actively controllable elements in this robot. For this type of robots, wheel-slip could offer a lot of hindrance while traversing on uneven terrains. Therefore, an effective wheel-torque controller is desired that will also improve the wheel-odometry and minimize power consumption. In this work, an optimal wheel-torque controller is proposed that minimizes the traction-to-normal force ratios of all the wheels at every instant of its motion. This ensures that, at every wheel, the least traction force per unit normal force is applied to maintain static stability and desired wheel speed. The lower this is, in comparison to the actual friction coefficient of the wheel-ground interface, the more margin of slip-free motion the robot can have. This formalism best exploits the redundancy offered by a modularly designed robot. This is the key novelty of this work. Extensive numerical and experimental studies were carried out to validate this controller. The robot was tested on four different surfaces and we report an overall average slip reduction of 44% and mean wheel-torque reduction by 16%.

Robust Wheel Torque Control for Traction/Braking Force Tracking Under Combined Longitudinal and Lateral Motion

Slip-ratio-based methods are commonly used to control the wheel torque such that the wheel dynamics is stabilized and the desired traction/braking force is attained; however, slip-ratio-based controllers are incompetent for precise longitudinal tire force tracking due to nonparametric tire model uncertainties. Force tracking performance further deteriorates whenever the tire is under combined longitudinal and lateral motion. In this paper, we propose an observer-based tire force control scheme that guarantees to achieve the desired longitudinal tire force accurately and robustly with respect to tire model uncertainties, changes in road conditions, and simultaneous lateral motion. Convergence of the force estimation and tracking errors is rigorously proved by the Lyapunov method. Then, simulations are conducted to verify the robust and accurate performance in longitudinal tire force estimation and tracking under a series of severe driving conditions.

Wheel Torque Distribution of Four-Wheel-Drive Electric Vehicles Based on Multi-Objective Optimization

The wheel driving torque on four-wheel-drive electric vehicles (4WDEVs) can be modulated precisely and continuously, therefore maneuverability and energy-saving control can be carried out at the same time. In this paper, a wheel torque distribution strategy is developed based on multi-objective optimization to improve vehicle maneuverability and reduce energy consumption. In the high-layer of the presented method, sliding mode control is used to calculate the desired yaw moment due to the model inaccuracy and parameter error. In the low-layer, mathematical programming with the penalty function consisting of the yaw moment control offset, the drive system energy loss and the slip ratio constraint is used for wheel torque control allocation. The programming is solved with the combination of off-line and on-line optimization to reduce the calculation cost, and the optimization results are sent to motor controllers as torque commands. Co-simulation based on MATLAB® and Carsim® proves that the developed strategy can both improve the vehicle maneuverability and reduce energy consumption.

Sources of power loss during torque-vectoring for fully electric vehicles

Continuous wheel torque control of fully electric vehicles (FEV) offers potential improvements in vehicle dynamics and energy efficiency. Various studies have shown benefits from torque–vectoring for minimising vehicle power consumption by considering the losses from the electric motor drives. However, during vehicle operation, various sources of power loss exist such as dissipations due to longitudinal and lateral tyre slip which are strongly influenced by the wheel torque control system. In this study, the different power loss types during steady–state and transient manoeuvres of a case study four–wheel–drive FEV are quantified. The motor drive losses are a major contributor at low lateral acceleration but represent a secondary factor at significant lateral acceleration at which the tyre slip power losses are the most significant contribution. Future control allocation methods seeking to reduce power consumption should consider tyre slip in addition to actuator losses.

Autonomous vehicle collision avoidance system using path planning and model-predictive-control-based active front steering and wheel torque control

Autonomous vehicles have attracted more attention in recent years as vehicle applications are evolving to a more intelligent and autonomous stage. This paper presents the development of a collision avoidance system for an autonomous vehicle application which consists of a motion planner and model-predictive-control-based active vehicle steering and active wheel torque control. A motion planner, based on polynomial parameterization, determines a collision-free trajectory when a vehicle collision with obstacles is likely to happen. Then an MPC-based control system controls the front steering and individual wheel torques to track the desired collision-free reference trajectory. The proposed system is evaluated through simulation, using an eight-degrees-of-freedom vehicle model with a ‘magic formula’ tire model, active front steering, and active wheel torque distribution systems. The simulation results show that it effectively performs collision avoidance maneuvers.

Independent wheel torque control of 4WD electric vehicle for differential drive assisted steering

In-wheel motors have tremendous potential to create an advanced all-wheel drive system. In this paper, a novel power assisted steering technology and its torque distribution control system were proposed, due to the independent driving characteristics of four-wheel-independent-drive electric vehicle. The first part of this study deals with the full description of the basic theory of differential drive assisted steering system. After that, 4-wheel-drive (4WD) electric vehicle dynamics model as well as driver model were built. Furthermore, the differential drive assisted steering control system, as well as the drive torque distribution and compensation control system, was also presented. Therein, the proportional–integral (PI) feedback control loop was employed to track the reference steering effort by controlling the drive torque distribution between the two sides wheels of the front axle. After that, the direct yaw moment control subsystem and the traction control subsystem were introduced, which were both employed to make the differential drive assisted steering work as well as wished. Finally, the open-loop and closed-loop simulation for validation were performed. The results verified that, the proposed differential drive torque assisted steering system cannot only reduce the steering efforts significantly, as well as ensure a stiffer steering feel at high vehicle speed and improve the returnability of the vehicle, but also keep the lateral stability of the vehicle.

Active driveline torque-management systems

This article reviews various individual wheel torque control technologies for active automotive safety systems. The use of active drive torque-management for vehicle stability control is a relatively new technology that is still being developed by researchers and automotive manufacturers. Current approaches and effects in various types of devices and drivelines were discussed. Control strategies for cornering performance and vehicle yaw and roll stability related to active torque-management systems were investigated. Three major types of ADTM devices, namely, center couplings, ELSDs, and torque-vectoring systems, were described, and the models, control system design, and limitations of each were discussed.

Skid Steering-Based Control of a Robotic Vehicle with Six in-Wheel Drives

This paper describes a driving control algorithm based on a skid steering for a robotic vehicle with articulated suspension (RVAS). The RVAS is a kind of unmanned ground vehicle based on a skid steering using an independent in-wheel drive at each wheel. The driving control algorithm consists of four parts: a speed controller for following a desired speed, a lateral motion controller that computes a yaw moment input to track a desired yaw rate or a desired trajectory according to the control mode, a longitudinal tyre force distribution algorithm that determines an optimal desired longitudinal tyre force, and a wheel torque controller that determines a wheel torque command at each wheel in order to keep the slip ratio at each wheel below a limit value as well as to track the desired tyre force. Longitudinal and vertical tyre force estimators are required for the optimal tyre force distribution and wheel slip control. A dynamic model of the RVAS for simulation study is developed and validated using the vehicle test data. Simulation and vehicle tests are conducted in order to evaluate the proposed driving controller. It is found from simulation and vehicle test results that the proposed driving controller provides a satisfactory motion control performance according to the control mode.

Design, implementation, and test of skid steering-based autonomous driving controller for a robotic vehicle with articulated suspension

This paper describes an autonomous driving control algorithm based on skid steering for a Robotic Vehicle with Articulated Suspension (RVAS). The driving control algorithm consisted of four parts: speed controller for following the desired speed, trajectory tracking controller to track the desired trajectory, longitudinal tire force distribution algorithm which determines the optimal desired longitudinal tire force and wheel torque controller which determines the wheel torque command at each wheel to keep the slip ratio below the limit value as well as to track the desired tire force. The longitudinal and vertical tire force estimators were designed for optimal tire force distribution and wheel slip control. The dynamic model of the RVAS is validated using vehicle test data. Simulation and vehicle tests were conducted in order to evaluate the proposed driving control algorithm. Based on the simulation and test results, the proposed driving controller was shown to produces satisfactory trajectory tracking performance.

Multivariable torque tracking control for E-IVT hybrid powertrain

This study deals with the control of a hybrid vehicle powertrain, composed of three actuators (one engine, two electric machines). This powertrain belongs to the electric-infinitely variable transmission class. In order to achieve low fuel consumption, drivability and electric power management, controllers must achieve simultaneously three specifications: tracking engine speed, wheel-torque and battery power references. Decoupled controlled-output behaviours and maximal performances are also required. In order to imitate a classical powertrain control structure, the control structure is split into two parts. The interest is to decouple transmission speed ratio control and wheel torque control. A model-based design approach is proposed, that directly deals with robustness and decoupling, in a full multivariable and frequency-dependent framework (H ∞ synthesis). Closed-loop simulations are presented. Stability and performances faced to disturbances and non-linearities are also evaluated, using the theory of linear parameter varying systems.