In-wheel Motor Electric Vehicle Research Articles

Vertical vibration control to the in-wheel-motor electric vehicles with static eccentricity based on a reinforcement learning method

The in-wheel-motor electric vehicle (IWM-EV) is hailed as the epitome of driving ingenuity within the realm of electric vehicles. Nonetheless, the intricate nature of its components, compounded by the intricate interplay of multiple force fields, poses a significant detriment to ride comfort. In the present study, an IWM-EV driven by a permanent magnet synchronous motor was employed as a representative case study. Initially, the calculations were conducted to determine the unbalanced magnetic force (UMF) in the presence of static eccentricity of the stator. Subsequently, the characteristics of UMF across different ratios of static eccentricity as well as different velocities in the time domains were analyzed. Furthermore, the road-electromagnetic-mechanical model was developed to investigate the influence of UMF on the vertical vibration of IWM-EV under static eccentricity, comparing it against the scenario devoid of UMF. Finally, a reinforcement learning control approach was adopted to regulate the active suspension system, comparing its efficacy with that of passive suspension and semi-active suspension (specifically, skyhook control). Through extensive simulations, the results demonstrated that the reinforcement learning control strategy derived from the road-electromagnetic-mechanical model outperforms the other two control strategies, exhibiting commendable resilience and adaptability across diverse road surfaces and velocities. This study unveiled the potential of RL methods in enhancing riding comfort through active suspension control.

Design of ABS sliding mode control system for in-wheel motor vehicle based on road identification

Aiming at the problem that the current Anti-lock Braking System (ABS) control algorithm can not make full use of the ground friction to complete the braking when emergency braking on complex roads, an ABS sliding mode control method based on road surface identification is proposed. Combined with the in-wheel motor of in-wheel motor electric vehicle, a coordinated control method of motor regenerative braking and mechanical friction braking is designed. Based on the neural network control method, the road friction coefficient is estimated to realize the identification of typical roads and dynamically obtain the optimal slip ratio of different roads. The ABS sliding mode controler is designed with the optimal slip ratio and the actual slip ratio as input, and the saturation function is used to replace the symbol function in the traditional sliding mode control to weaken the chattering problem, and then the ABS controller is designed. The research results show that compared with the traditional ABS sliding mode controller, the designed ABS neural network sliding mode controller has the following advantages: 1. Through the identification of tire-road friction coefficient by neural network, the real-time performance and road adaptability of ABS controller are improved; 2. When the braking simulation is carried out at a given speed, the braking time is reduced by about 1.03 % and the braking distance is shortened by about 1.01%; 3. The identification of tire-road friction coefficient is realized, which weakens the chattering problem of traditional sliding mode control and improves the stability and robustness of ABS controller.

A Novel Magnetic-Geared Motor Combining Magnetic Gear and SR Motor

A direct-drive permanent magnet (PM) motor and a magnetic-geared PM motor have the advantage of high torque density. Therefore, these motors are expected to be applied as in-wheel motors for electric vehicles (EVs). However, they have a problem that it is difficult to achieve the wide speed-torque characteristics required for EVs. This paper presents a novel magnetic-geared motor that consists of a flux-modulated type magnetic gear and a switched reluctance (SR) motor. In this paper, the SR motor part and the magnetic gear part are designed, and both parts are combined into a magnetic-geared motor. The proposed magnetic-geared motor has the wide speed-torque characteristic, which direct-drive PM motors or SR motors cannot achieve.

Design of ABS sliding mode control system for in-wheel motor vehicle based on road recognition

Aiming at the problem that the current ABS control algorithm cann’t make full use of the ground braking force to complete the braking when the complex road surface is in emergency braking, the ABS sliding mode variable structure control method based on road surface identification is proposed. Combined with the in-wheel motor of in-wheel motor electric vehicle, a coordinated control method of motor hydraulic composite is designed. Based on the fuzzy logic control method, the road adhesion coefficient is estimated to realize the identification of typical roads and dynamically obtain the optimal slip rate of different roads. The ABS sliding mode variable structure controller is designed with the optimal slip ratio and the actual slip ratio as input, and the saturation function is used to replace the sign function in the traditional sliding mode variable structure control to weaken the ’ chattering ’ phenomenon in the sliding mode variable structure control, and then the ABS controller is designed. Taking the experimental prototype vehicle driven by four-wheel hub motor as the research object, an eight-degree-of-freedom dynamic simulation model of the whole vehicle is established. Compared with the traditional PID controller, the braking time is shortened by 0.2 s and the braking distance is shortened by 2.3 m, which shows the feasibility of the designed controller. Through the simulation braking experiment of the docking road, the adaptability and real-time performance of the ABS sliding mode controller are verified, and the importance of the road adhesion coefficient identification to the ABS controller is verified.

Development of Experimental Teaching Platform for In-Wheel Motor Electric Vehicle On-Board Testing

Background: The on-board test system is the key technology of in-wheel motor electric vehicles, which plays a vital role in the safety of the driver and the efficient operation of the vehicle. Methods: Based on the requirements of the current in-wheel motor electric vehicle experiment teaching content, this research develops an in-wheel motor electric vehicle experimental teaching platform based on Matlab/Simulink and LabVIEW to meet the current needs of the in-wheel motor electric vehicle experiment teaching content. Results: The vehicle speed, sideslip angle, and road adhesion coefficient can be accurately estimated using the vehicle test platform developed in the article. Conclusion: With accurate experimental results, the functionality, value, and teaching value of the in-wheel motor electric vehicle experimental teaching platform were fully verified.

New Method to Coordinate Vibration Energy Regeneration and Dynamic Performance of In-Wheel Motor Electrical Vehicles

A new method including suspension and wheel vibration energy regeneration is proposed in this study to coordinate the contradiction between vibration energy regeneration and dynamic performance of in-wheel motor electric vehicles (IWM-EVs). The influence mechanism of unsprung mass on the dynamic characteristics of IWM-EVs is investigated from the perspective of energy flow, and potential of energy regeneration of IWM-EVs is explored on this basis. A parameter sensitivity analysis of the proposed new method is conducted, and the optimal parameters are determined for a comparative simulation analysis among focus-driven electric vehicles, IWM-EVs, and IWM-EVs with linear electromagnetic dynamic vibration absorber (LEM-DVA). Results show that the proposed new method effectively improves the dynamic performance and achieves coordination between energy regeneration and dynamic performance despite its reduction of the vibration energy regeneration potential of IWM-EVs. A new structure, which integrates a linear electromagnetic damper (LEMD) and a LEM-DVA, is then proposed to implement the coordination method. The equivalent prototype and control system are designed for a hardware-in-the-loop test. The test results show good agreement with that of simulation despite some errors. This finding proves the effectiveness of the new structure in coordinating the vibration energy regeneration and dynamic performance of IWM-EVs.

Model Predictive Control for Energy-Efficient Yaw-Stabilizing Torque Vectoring in Electric Vehicles With Four In-Wheel Motors

This paper considers the problem of stabilizing and energy-efficient torque vectoring for electric vehicles with four independent in-wheel motors. In electric vehicles with four in-wheel motors, four electric motors are separately attached to the four wheels without an extra drive shaft. The mechanical and structural nature enables reduction of energy loss during power transmission and securing extra interior space. In addition, independent control of wheel torques can provide better yaw motion stability and improved energy efficiency. This paper proposes two model predictive control (MPC) methods for stability-constrained energy-efficient torque vectoring of four in-wheel motor electric vehicles. For the adaptive weighting factors of multiple objective functions of reference tracking and energy saving, we use exponential functions that vary with the lateral motion and steering input. Depending on the optimal control problem formulation with different dynamical system equations and constraints, the associated predictive controller can be represented as either a linear parameter-varying MPC (LPV-MPC) or nonlinear MPC (NMPC). For LPV-MPC, longitudinal and lateral motions are decoupled, whereas the coupled dynamics of the two-track model are exploited in NMPC. For comparisons and demonstrations of LPV-MPC and NMPC in the MPC of torque vectoring, three driving scenarios are simulated with a high-fidelity vehicle simulation solution, CarMaker (IPG Automotive). In comparison with the built-in IPG driver implemented in CarMaker, we demonstrate fuel efficiency improvements of over 2–3 % on average with guaranteed yaw stability.

Review on Torque Distribution Scheme of Four-Wheel In-Wheel Motor Electric Vehicle

In-wheel motor electric vehicles have the advantages of independently controllable four-wheel torque, high energy utilization rate, and fast motor response speed, which greatly reduces the curb weight of the vehicle and simplifies the structure of the vehicle, making it an expert at home and abroad research hotspots. However, the in-wheel motor independently drives the electric vehicle. The in-wheel motor directly drives the vehicle, and the motion states of each wheel are independent of each other; that is, each wheel can be independently driven by wire control, which puts forward higher requirements for the torque distribution control of the entire vehicle. Starting from the driving form of the car, this paper focuses on the design of the torque distribution scheme of the in-wheel motor by experts and scholars in the past, such as the use of genetic algorithm, BP neural network, particle swarm algorithm, and fuzzy control algorithm to distribute the torque of the in-wheel motor, and the research on vehicle economy and stability under torque distribution optimization is reviewed. The future development direction of in-wheel motor torque distribution is prospected.

Research on Steering Stability Control of Electric Vehicle Driven by Dual InWheel Motor

The dual in-wheel motor electric vehicle has the advantages of fast response and high flexibility, while its stability and safety are more difficult to control. To study the stability control of the dual in-wheel electric vehicle when turning, firstly, the paper establishes the Ackerman model of the dual in-wheel electric vehicle, and controls the wheel speed and slip rate by the method of logical threshold value; then establishes the linear two degree of freedom model of the double hub electric vehicle, obtains the vehicle yaw moment and ideal yaw rate by using the mathematical formula, and controls the wheel speed and slip rate by the sliding mode control. The moment is distributed so that the actual yaw rate keeps tracking the ideal value. The electronic differential control strategy of wheel slip rate and wheel yaw rate is established. Finally, the control strategy is simulated by MATLAB. The simulation results show that the proposed control strategy of slip rate and yaw rate can make the vehicle drive stably when turning

Trajectory tracking of in-wheel motor electric vehicles based on preview time adaptive and torque difference control

In order to improve the accuracy of trajectory tracking of in-wheel motor electric vehicles, a preview time adaptive trajectory tracking method based on iterative algorithm and fuzzy control is proposed. Firstly, based on the vehicle’s three-degree-of-freedom model, the vehicle is controlled to track trajectory based on model predictive control (MPC). The preview step size and sampling period of MPC are adjusted by iterative function and fuzzy controller, respectively. Then, In order to optimize MPC active steering control, a differential torque controller is established to realize the trajectory tracking control of differential torque steering. Finally, Carsim/Simulink co-simulation analysis and real vehicle verification are done. The simulation results show that the controller can complete the trajectory tracking control of the in-wheel motor intelligent vehicle, and the stability and steering performance are good. The controller has good robustness and adaptability according to road adhesion conditions and vehicle speed changes. At the same time, the trajectory tracking accuracy of the MPC controller is better than sliding mode variable structure control (SMC). The real vehicle verification results show that when the real vehicle tracking under different speeds, the adaptive preview time controller designed in this paper has good trajectory tracking performance and stability.

Design and Optimization of an In-wheel Unequal Stator Teeth Motor

Recently, many researches have been focusing on finding new machine topologies that maximize the efficiency and minimize the mass of in-wheel motors for electric vehicles. This paper presents the design and the optimization of a new in-wheel motor for electric vehicles. This was achieved by proposing a new topology including unequal stator teeth. The design of the machine was performed with an analytical model that considers the slotting effect and the saturation when calculating the air gap flux density. The main purpose of the optimization process is to determine the optimal machine geometric dimensions. This optimization was performed according to three objective functions while respecting a set of constraints. The first objective function is to maximize the machine’s efficiency, the second is to minimize the mass, and the third is to minimize the torque ripple. In this regard, four multiobjective optimization algorithms were employed: two of them belong to the particle swarm optimization family, and the others are genetic algorithms. An optimized machine design was chosen and analyzed using finite element analysis (FEA). The comparison of FEA and optimization results showed a good agreement between both of them, and proves the validity of the proposed design.

Stator vibration analysis of in-wheel motor for electric vehicle based on harmonic response analysis method

Stator vibration analysis of in-wheel motor for electric vehicle based on harmonic response analysis method

Study on reducing cogging torque and core loss of in-wheel motor for electric vehicle based on stator full-slot offset

Study on reducing cogging torque and core loss of in-wheel motor for electric vehicle based on stator full-slot offset

Study on reducing cogging torque and core loss of in-wheel motor for electric vehicle based on stator full-slot offset

Study on reducing cogging torque and core loss of in-wheel motor for electric vehicle based on stator full-slot offset

Stator vibration analysis of in-wheel motor for electric vehicle based on harmonic response analysis method

Stator vibration analysis of in-wheel motor for electric vehicle based on harmonic response analysis method

Individual Drive-Wheel Energy Management for Rear-Traction Electric Vehicles with In-Wheel Motors

In-wheel motor technology has reduced the number of components required in a vehicle’s power train system, but it has also led to several additional technological challenges. According to kinematic laws, during the turning maneuvers of a vehicle, the tires must turn at adequate rotational speeds to provide an instantaneous center of rotation. An Electronic Differential System (EDS) controlling these speeds is necessary to ensure speeds on the rear axle wheels, always guaranteeing a tractive effort to move the vehicle with the least possible energy. In this work, we present an EDS developed, implemented, and tested in a virtual environment using MATLAB™, with the proposed developments then implemented in a test car. Exhaustive experimental testing demonstrated that the proposed EDS design significantly improves the test vehicle’s longitudinal dynamics and energy consumption. This paper’s main contribution consists of designing an EDS for an in-wheel motor electric vehicle (IWMEV), with motors directly connected to the rear axle. The design demonstrated effective energy management, with savings of up to 21.4% over a vehicle without EDS, while at the same time improving longitudinal dynamic performance.

Design and experimental verification of self-powered electromagnetic vibration suppression and absorption system for in-wheel motor electric vehicles

A self-powered electromagnetic vibration suppression and absorption system integrated with a magnetorheological damper and a linear motor is designed to attenuate the negative effect of vertical vibration caused by the increased unsprung mass for in-wheel motor electric vehicles in this article. The magnetorheological damper is used as a suspension damper to suppress body vibration, and linear motor is used as a dynamic vibration absorber, namely, linear electromagnetic dynamic vibration absorber, to absorb tire vibration, and regenerates the vibration power to drive the magnetorheological damper, realizing self-power. Based on power flow theory, the power transfer mechanism of the vertical vibration for in-wheel motor electric vehicles and the regeneration potential are analyzed. The negative effect on the dynamic performance of in-wheel motor electric vehicles is analyzed through the root mean square of dynamic responses. Moreover, the specific structure scheme of the self-powered electromagnetic vibration suppression and absorption system is provided. The influence of system mass, stiffness, and damping of the linear electromagnetic dynamic vibration absorber on the dynamic performance is analyzed, and these parameters are optimized by particle swarm optimization. Simulation results show that in comparison with a passive damper, the self-powered electromagnetic vibration suppression and absorption system can reduce the body acceleration by 17.05%, which is better than the magnetorheological damper (10.08%). The self-powered electromagnetic vibration suppression and absorption system increases the tire dynamic load by 5.62%, but it is 8.68% less than the magnetorheological damper. Additionally, the regenerated power can offset the consumed power adequately to realize self-power. Finally, a bench test is conducted to verify the effectiveness and feasibility of the self-powered electromagnetic vibration suppression and absorption system.

Design and Analysis of a Water-Cooling System in a New Yokeless and Segmented Armature Axial In-Wheel Motor for Electric Vehicles

Abstract An in-wheel motor, as a key part of an in-wheel driving system, needs to satisfy strict restrictions on thermal balance for increasingly high-power density in limited space and weight. Therefore, a new in-wheel motor with an innovative water-cooling system for one newly developed electric vehicle was developed. Based on the mechanical structure of the motor, all potential water-cooling layouts were first designed with consideration of mechanical strength and manufacturability. A thermal conjugate simulation model of the developed in-wheel motor was then built, and its thermally fluid–solid interactions were investigated in this study. All potential water-path layouts of the motor were compared regarding the cooling effect and fluid resistance, which impact the performance of the motor. Fluid flow velocity and fluid state, determined by the water-path layout, significantly impact the cooling effect of the motor. The well-designed water-cooling system significantly reduces the motor’s temperature at a low cost on required coolant-driven pressure which benefits the efficiency of the developed motor. A prototype of the developed motor with the optimal water-path layout was built and tested on the test rig. The developed motor provides outstanding thermal performance.

Research on Dynamic Performance Simulation of In-wheel Motor Electric Vehicle Based on CarSim-Simulink

In order to reduce test costs and improve work efficiency, on the basis of the existing in-wheel-motor electric vehicle platform, CarSim software is used to establish a complete in-wheel-motor electric vehicle model that matches the actual vehicle. Based on Simulink, the dynamic model of the in-wheel motor is established. By defining the interface between the vehicle and the motor drive system, a joint simulation platform for in-wheel motor electric vehicles is established based on CarSim-Simulink, and simulation verification is performed on it. The results show that the established simulation model has high accuracy, can better simulate the existing experimental vehicle, accurately reflect the dynamic performance response of the vehicle, and provide a basis for further research and verification of control algorithms.

A new criterion for comfort assessment of in-wheel motor electric vehicles

A novel optimization technique was implemented to investigate the effects of vibrations on comfort of occupants to maintain oscillations in an acceptable zone in accordance with the International Organization for Standardization 2631 standard. In this regard, a newly introduced comfort indicator was defined as discomfort criterion (DiC). The effectiveness of the proposed measure was investigated throughout the suspension optimization of an in-wheel motor electric vehicle which almost doubled the unsprung mass by adding an electric motor to the wheel assembly. First, a spatial oscillatory model of the electric vehicle with eight degrees of freedom was developed, and the linear quadratic regulator control scheme is selected to control an actuator in an active suspension. Road excitations were then generated by applying the power spectral density of road class B–C provided by the International Organization for Standardization 8608 standard. The exceedance from the reduced comfort limit (in accordance with the International Organization for Standardization 2631 standard) and wheel travel (WT) of the vehicle were considered as design objectives. Finally, using a novel optimization procedure, the optimum condition and impact factor of the design variables, as well as counterplots of the design objectives with respect to the effective design parameters, were extracted and analyzed. Results proved the proposed indicator, that is, discomfort criterion (DiC) as a reliable measure to assess suspension systems’ performance effectively.