Driving Torque Distribution Research Articles

Optimal powertrain system design and V2V and V2I based hierarchical control strategy of FRIDEV under vehicle-following scenarios

In this paper, the front- and rear-independent-drive electric vehicle (FRIDEV) is selected as the target vehicle for its good dynamic and economy performance. Based on the analysis of the cost, efficiency, and loss characteristics of different motors, the interior permanent magnet synchronous motor (IPMSM) and induction motor (IM) are applied in the target powertrain system. Then, the proposed powertrain system is optimized based on the analysis of driving cycles. The optimal control strategy for the target powertrain system is developed, which consists of the driving mode switching algorithm and the driving torque distribution based on adaptive particle swarm optimization (APSO). Furthermore, in order to achieve the efficient autonomous driving of the target vehicle under the vehicle-following scenarios, a hierarchical control strategy is proposed with the combination of upper-level control of the speed planning strategy and the lower-level control of powertrain system control strategy. The upper-level control of speed planning strategy is designed, which can determine and track the target vehicle speed based on the information from vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communications. Finally, simulation analysis in MATLAB/Simulink and virtual driving experiments are conducted to verify the superiority of the proposed powertrain system and hierarchical control strategy.

Research on Optimal Driving Torque Control Strategy for Multi-Axle Distributed Electric Drive Heavy-Duty Vehicles

Multi-axle distributed electric drive heavy-duty vehicles have the characteristics of high transmission efficiency, strong maneuverability, and good passability, making them widely used in large cargo transportation. However, the current driving torque control strategies of multi-axle distributed electric drive heavy-duty vehicles lack comprehensive consideration of their longitudinal and lateral dynamic characteristics, making it difficult to comprehensively optimize multiple performances such as power economy, comfort, and stability. In order to solve the above problems, This work focuses on a five-axle distributed electric drive heavy-duty vehicle. Firstly, given the differences in dynamics between two-axle vehicles and multi-axle vehicles, the dynamic model of the multi-axle distributed electric drive heavy-duty vehicle and its critical components is constructed. Then, by analyzing the characteristics of power economy, comfort, and stability of the multi-axle distributed electric drive heavy-duty vehicle, an optimal driving torque control strategy based on multiple performance coordination is proposed. Finally, on the hardware-in-the-loop (HiL) platform, the performance of the optimal driving torque control strategy proposed in this paper is verified by using the China Heavy-Duty Commercial Vehicle Test Cycle for Truck (CHTC-HT) and a straight-line acceleration driving condition on a split friction road. The simulation test results show that, compared with the traditional torque average distribution strategy, the proposed optimal driving torque control strategy can reduce the energy consumption rate by 3.45% in CHTC-HT. The strategy is attributed to the driving torque distribution based on the vehicle’s optimal instantaneous energy consumption, and vehicle comfort is also ensured by the driving mode switching frequency suppression. Subsequently, the vehicle’s stability on the split friction road is effectively improved by the torque coordination compensation strategy. This control strategy significantly improves the comprehensive performance of multi-axle distributed electric drive heavy-duty vehicles.

Co-optimization energy management strategy for a novel dual-motor drive system of electric tractor considering efficiency and stability

The challenge in developing an electric tractor control strategy lies in operating efficiently and smoothly in most conditions. This paper put forward a co-optimization energy management strategy (EMS) for dual-motor electric tractors to achieve working efficiency and smoothness simultaneously in typical conditions including ploughing, rotary tillage and transportation. Firstly, the mathematical models for components of the drive system are established, such as the power transfer model and gear shifting model. Secondly, the novel EMS combining demand torque calculation method (DTCM) and driving torque distribution strategy (DTDS) is proposed, which is based on nonlinear PID control and modified snake optimizer (SO) algorithm respectively. Then, the hardware in the loop (HIL) platform is manufactured, and load data for the HIL test collecting by a tractor operating in the field. Finally, the performances of the electric tractor with the novel EMS in three typical conditions are validated. It shows that EMS can identify the demand torque accurately. Compared to the rule-based algorithm with reasonable parameters, the novel EMS improves efficiency and stability significantly, especially in ploughing increasing efficiency by 14.44% and decreasing jerk fluctuates by 73.33%. The research results can provide theoretical references for developing the EMS of the electric tractor.

EV Smart Regeneration using Super Capacitor with Battery Bank

A EV is defined as a vehicle that can be powered by an electric motor that draws electricity from a battery and is capable of being charged from an external source. The biggest factor that determines the range of an EV is the capacity of the lithium-ion battery in the car. This paper proposes a real time optimal driving torque distribution strategy for an electric vehicle (EV) with independently driven front and rear wheels. The proposed optimal torque distribution strategy among the front and rear wheels, improves the overall energy efficiency of the vehicle, there by increasing the driving range achievable per charge cycle of the EV. The torque is optimized with the objective of minimizing the energy consumption during driving as well as maximizing the regenerative energy recuperation during the braking. Here, a real time torque distribution control system is proposed which can realize optimal distribution of driving-braking torque corresponding to the driving commands, for constant speed driving, acceleration, braking and grade climbing driving modes. The optimal torque distribution ensures minimal energy consumption, thus improving the energy efficiency of the EV. By reducing the energy consumption the driving range achievable per charge cycle is improved, realizing range extension of EV.

Design of an Adaptive Distributed Drive Control Strategy for a Wheel-Side Rear-Drive Electric Bus

A wheel motor simplifies the chassis structure of an electric bus, greatly improving its response speed and controllability. How to improve the lateral stability of the vehicle under complex and changeable driving conditions is a major problem in the motion control of electric buses. This study proposed an adaptive distributed drive control strategy for a rear-wheel drive electric bus. An adaptive fuzzy controller was designed to obtain the additional yaw moment of the vehicle and then combined with a rule distribution method to modify the steering characteristics of the vehicle to obtain the optimal driving torque distribution. Hardware-in-the-loop test results showed that under adaptive fuzzy control, the yaw rate deviations under low- and high-speed conditions were reduced from 18% and 42% without control to 10% and 23% with control, respectively. Under sine wave conditions, the deviation of the yaw rate and the vehicle’s sideslip angle were reduced from 83% and 852% without control to 12% and 15% with control, respectively. It was verified that the electric bus with adaptive fuzzy control could maintain good vehicle stability at full speed.

Driving Torque Distribution Strategy of Skid-Steering Vehicles with Knowledge-Assisted Reinforcement Learning

Due to the advantages of their drive configuration form, skid-steering vehicles with independent wheel drive systems are widely used in various special applications. However, obtaining a reasonable distribution of the driving torques for the coordinated control of independent driving wheels is a challenging problem. In this paper, we propose a torque distribution strategy based on the Knowledge-Assisted Deep Deterministic Policy Gradient (KA-DDPG) algorithm, in order to minimize the desired value tracking error as well as achieve the longitudinal speed and yaw rate tracking control of skid-steering vehicles. The KA-DDPG algorithm combines knowledge-assisted learning methods with the DDPG algorithm, within the framework of knowledge-assisted reinforcement learning. To accelerate the learning process of KA-DDPG, two assisted learning methods are proposed: a criteria action method and a guiding reward method. The simulation results obtained, considering different scenarios, demonstrate that the KA-DDPG-based torque distribution strategy allows a skid-steering vehicle to achieve high performance, in tracking the desired value. In addition, further simulation results, also, demonstrate the contributions of knowledge-assisted learning methods to the training process of KA-DDPG: the criteria action method speeds up the learning speed by reducing the agent’s random action selection, while the guiding reward method achieves the same result by sharpening the reward function.

Design of an Anti-Windup PID Algorithm for Differential Torque Steering Systems

The EV (electric vehicle) with a wheel hub motor has the advantage of independent driving torque distribution for each wheel, which allows the vehicle performance to be improved. Therefore, a lot of work has been done to investigate the torque allocation algorithm for the mechanical and differential torque integration steering system. To investigate the differential steering process, the 2 DOF (degree of freedom) dual-track reference models with linear and nonlinear tire models are established, and based on the steering process analysis and yaw rate gain calculation, a BP-NN (backpropagation neural network) model is initiated to maintain the accuracy of the calculated yaw rate gain. The limitation of DTSS (differential torque steering system) and the difference of reference models with linear and nonlinear tires are drawn. In addition, an anti-windup variable PID (proportion integration differentiation) controller is designed for the torque distribution. Based on the built 8 DOF model, the vehicle performance indicators are calculated and compared, the gap between the models with linear and nonlinear tires is non-negligible, and a reference model with a nonlinear tire model is recommended for the relevant research. The anti-windup variable PID controller has a better performance than the normal PID controller except for the stability phase plane indicator.

Study on the Control of Torque Distribution of 4WD Corn Harvester Operation Drive

In response to the poor adaptability of existing harvesters to complex operating conditions in the field, this study took a three-row four-wheel-drive (4WD) corn harvester as the research object, designed a traveling transmission system layout, proposed a control strategy of driving torque distribution, simulated, and analyzed each of the four states of harvester drive wheels slippage. The results showed that under the driving wheels slipping condition, after applying torque control, the adjustment time was 43.3% shorter than that without control in the case of single wheel slipping, 11.1% shorter than that without control in the case of two wheels slipping on the same axle, 41.4% shorter than that without control in the case of two wheels slipping on different axles, and 36.6% shorter than that without control in the case of three driving wheels slipping. The application of drive torque distribution control could significantly improve the traction and passing ability of the corn harvesters during operation, as well as made the harvester travel more smoothly, thus improving the harvest quality. The drive torque distribution control can be applied not only to the three-row corn harvester, but also to other types of harvesters, and self-propelled agricultural machinery to enhance their adaptability, improving their operation quality. It has a significant reference value for the development of the driving system on walking agricultural machinery.

Motor shifting and torque distribution control of a multi-motor driving system in electric construction vehicles

With the rapid development of the world economic construction and the shortage of energy, it has become a hot research issue to realize the electrification of the vehicle driving system and improve energy efficiency. Most of the electric construction machinery power systems are characterized by low speed and high load. The coordinated driving of multiple motors can increase the output torque and improve the transmission efficiency of the machine on the basis of a compact layout. A novel configuration of electric construction vehicles based on multi-motor and single-speed and its driving torque distribution control method is presented in this paper. The detailed mathematical model is established and the simulation analysis is carried out based on it. The results show that the proposed multi-motor driving system with the control strategy can improve the overall efficiency in the condition of ensuring the driving force when the parameter matching and motors choosing reasonably.

Enhancement of vehicle stability based on coordinated active rear steering and additional yaw moment

To improve the handling and manoeuvrability of four-wheel steer (4WS) and in-wheel motor-driven electric vehicle (EV) under critical conditions, a coordinated control method combining active rear-wheel steering (ARS) and additional yaw moment control in the form of additional drive torque distribution is proposed. Considering the nonlinear properties of tyre force, a nonlinear model predictive controller (NMPC) is designed to track the desired yaw rate and constrain the sideslip angle. Meanwhile, the actuator and security constraints are satisfied effectively. Finally, the control performance is investigated by co-simulation with MATLAB/Simulink and CarSim. The results show that the vehicle longitudinal and lateral stability are both efficiently enhanced under extreme conditions.

Optimal Coordinated Control of ARS and DYC for Four-Wheel Steer and In-Wheel Motor Driven Electric Vehicle With Unknown Tire Model

To improve the handling and maneuverability of four-wheel steer (4WS) and in-wheel motor driven electric vehicle (EV) in which the mechanical properties of tires are unknown, an optimal coordinated control combining active rear wheel steering (ARS) and direct yaw moment control (DYC) in the form of active drive torque distribution is proposed. By designing a new type of particle filter (PF), the online identification of unknown tire model is realized and its uncertainties and road surface disturbances are both considered. The constraints of vehicle motions tracking ideal values are derived according to the estimated tire lateral forces with Lyapunov stability theory. And then based on the thought of backstepping and optimization, the drive torque distribution method and the rear wheel steer strategy are obtained aiming at minimizing tire load and control inputs, which also take the effective working range of in-wheel motor into account. Finally, the validity and practicability of overall controller are verified through the simulation of Carsim and Matlab/Simulink. The proposed control strategy lays a theoretical foundation for the integration and optimization of 4WS EVs driven by in-wheel motors.

Distribution of driving force beneath wheeled vehicle with varying center of gravity

Driving force analysis is performed on the no-spin differential and full-time all-wheel-drive vehicle; this thesis takes an automatic loading mixing vehicle as an example to introduce the compositions and working principle of the driving system. Based on the tire-ground mechanics, the model of the dynamics and the kinematics is established under the walking straight and steering conditions. According to the theoretical model, the influence of the vehicle’s gravity center on the moving system is analyzed. Co-simulation based on LMS Imagine Lab AMESim and LMS Virtual Lab Motion is performed to build the hydraulic driving system and the multi-body dynamics system models. Based on the tire-ground load environment simulation model built by 1D + 3D, various positions of the gravity center of the model are set to compare with the theoretical analysis. Various weight blocks are also added to change the location of the gravity center in the practical experiment. The conclusions that different gravity center positions lead to the change of the driving torque distribution are proved by the simulation results and experimental data.

Adaptive equivalent consumption minimisation strategy and dynamic control allocation-based optimal power management strategy for four-wheel drive hybrid electric vehicles

An adaptive equivalent consumption minimisation strategy and dynamic control allocation-based optimal power management strategy for a four-wheel drive plug-in hybrid electric vehicle is proposed in this paper. The equivalent factors of adaptive equivalent consumption minimisation strategy are optimised offline based on ISIGHT software over several typical driving cycles, which is integrated with AVL CRUISE and MATLAB/Simulink. To update the equivalent factor adaptively according to the predictive velocity, a neural network-based optimal equivalent factor prediction model is built, which can be used online. The torque distribution strategy considering axle load based on energy management strategy optimisation results and the vehicle dynamics control distribution is proposed: this includes two-wheel drive torque distribution, four-wheel drive torque distribution and brake torque distribution. The proposed energy management strategy is verified in New European Driving Cycle and Worldwide harmonised Light Vehicle Test Cycle driving patterns, and the simulation results show that the fuel economy of adaptive equivalent consumption minimisation strategy and dynamic control allocation-based optimal power management strategy is improved by 8.84% and 7.52% in New European Driving Cycle and Worldwide harmonised Light Vehicle Test Cycle, respectively, compared with the benchmark algorithm-based strategy.

Modeling and Simulation of Off-Road Vehicle Mobility with Driving Torque Distribution Control on Split Adhesion Conditions

This paper presents a theoretical model for simulation of driving torque distribution control to improve off-road vehicle mobility on split adhesion conditions. The model is constructed and then validated with experimental test rig results. A MATLAB simulink modeling of an electronically controlled device is used to modulate the applied force over multi-plate clutches located between the automotive driven axle shafts and the stationary hub. On driving over split adhesion roads, the control device brakes the spinning axle wheel running over ground low adhesion side and accordingly biases more torque to the other wheel with good adhesion side. This would improve the vehicle off-road mobility and save the power losses on low adhesion wheels. The proposed control model had been validated with experimental results obtained from an experimental tests conducted on a specially designed and built test rig. Consequently, the proposed control system has been embedded within a full car theoretical model to predict the vehicle performance on split adhesion drive conditions. The results showed that the constructed simulink model is suitable for simulating the proposed controlled device for torque distribution after matching the simulation results with experimental test rig results. Moreover, the proposed control model could be implemented to improve the transmitted traction power to the road from a conventional deferential.

Lateral Stability Control of 4WD Vehicle considering Ride Performance

In order to improve the lateral stability of 4WD vehicle and guarantee its ride performance, this study designs target yaw control system based on sliding mode variable structure control, proposes driving torque distribution control algorithm based on the response of vehicle stable steering characteristic, and designs semiactive suspension control system based on double-fuzzy controller. The control performance is analyzed during the step steering and the split-µ road turning. The results indicate that the combined control system is able to improve the lateral stability of this 4WD vehicle during turning, reduce its body vibration acceleration and suspension dynamic deflection during travelling on bumpy and uneven road, guarantee its dynamic property, and improve its comprehensive performance.

Driving and Braking Torque Distribution Methods for Front- and Rear-Wheel-Independent Drive-Type Electric Vehicles on Roads With Low Friction Coefficient

This paper focuses on the development of a front- and rear-wheel-independent drive-type electric vehicle (EV) (FRID EV) as a next-generation EV. The ideal characteristics of a FRID EV promote good performance and safety and are the result of structural features that independently control the driving and braking torques of the front and rear wheels. The first characteristic is the failsafe function. This function enables vehicles to continue running without any unexpected or sudden stops, even if one of the propulsion systems fails. The second characteristic is a function that performs efficient acceleration and deceleration on all road surfaces. This function works by distributing the driving or braking torques to the front and rear wheels, taking into consideration load movement. The third characteristic ensures that the vehicle runs safely on roads with a low friction coefficient (μ), such as icy roads. In this paper, we propose a driving torque distribution method when cornering and a braking torque distribution method; these methods are related to the third characteristic, and they are particularly effective when driving on roads with ultralow μ. We verify the effectiveness of the proposed torque control methods through simulations and experiments on the ultralow-μ road surface with a μ of 0.1.

Driving Torque Distribution Method for Front-and- Rear- Wheel-Independent-Drive-Type Electric Vehicles (FRID EVs) at the Time of Cornering

This paper describes a driving torque distribution method for front–and-rear-wheel-independent-drivetype electric vehicles (FRID EVs) in which it is possible to get stable steering on a low friction coefficient road surface. This method is characterized by distributing driving torque to the left and right wheels of the front and rear wheels, considering not only load movement of the longitudinal direction but also load movement of the lateral direction which is generated at cornering. The load movements are estimated by detecting components of the 3-axis directions, i.e., longitudinal and lateral accelerations and yaw rate, and the steering angle and friction coefficient μ of the road surface. The effectiveness of the proposed driving torque distribution method was verified using simulators equivalent to the prototype FRID EV simulated with Matlab/Simulink and CarSim software. This method is expected to be indispensable to improving running performance of FRID EVs.

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.

Comparison of active systems for lateral drive torque distribution

Lateral torque distributing drive train systems allow the use of the adhesion potential adapted to the wheel load, which leads to a significant improvement of agility and vehicle performance especially in front-wheel drive applications. The Institute of Automotive Engineering of the Technische Universitat (TU) Braunschweig conducted a simulation analysis and systematic concept comparison of these systems.

Steer-by-wire system integrated with active braking and driving-torque distribution

Steer-by-wire system (SBW), which is expected to improve passive and active safety for vehicle, has been discussed. Fault-tolerant capability of SBW is similarly required to a fly-by-wire of airplane because failures of SBW have a possibility to cause lack of steering function of the vehicle. Redundancy and diversity of steering function tend to require high cost, and it can postpone commercialization of SBW. This paper describes a diversified architecture for SBW fault-tolerance and its management that is integrated with pre-installed ESC and DTD. Effectiveness of the architecture and the management is investigated by a driving simulator experiment. This study shows a possibility to achieve reliability without excessive redundancy or additional diversity of the steering function.