In-wheel Motor Research Articles

Studies Concerning Electrical Repowering of a Training Airplane Using Hydrogen Fuel Cells

The increase in greenhouse gas emissions, as well as the risk of fossil fuel depletion, has prompted a transition to electric transportation. The European Union aims to substantially reduce pollutant emissions by 2035 through the use of renewable energies. In aviation, this transition is particularly challenging, mainly due to the weight of onboard equipment. Traditional electric motors with radial magnetic flux have been replaced by axial magnetic flux motors with reduced weight and volume, high efficiency, power, and torque. These motors were initially developed for electric vehicles with in-wheel motors but have been adapted for aviation without modifications. Worldwide, there are already companies developing propulsion systems for various aircraft categories using such electric motors. One category of aircraft that could benefit from this electric motor development is traditionally constructed training aircraft with significant remaining flight resource. Electric repowering would allow their continued use for pilot training, preparing them for future electrically powered aircraft. This article presents a study on the feasibility of repowering a classic training aircraft with an electric propulsion system. The possibilities of using either a battery or a hybrid source composed of a battery and a fuel cell as an energy source are explored. The goal is to utilize components already in production to eliminate the research phase for specific aircraft components.

Lyapunov-based control system design for trajectory tracking in electrical autonomous vehicles with in-wheel motors

In this paper, a hierarchical three-layer control structure is presented for the vehicle’s path following. In the first layer, a Lyapunov-based control law is proposed for determining forces and torque required at the vehicle’s center of gravity that guarantees the convergence of tracking errors. Then, a feasible formulation is developed to distribute the longitudinal and lateral forces of the wheels. Each wheel’s forces are distributed in such a way that prevents saturation of that tire. In the third layer, a robust sliding mode control is developed to determine the driving/braking torques of each wheel. Finally, a co-simulation is performed using Carsim and MATLAB/Simulink to evaluate the performance of the proposed control system. The results show that the proposed algorithm is capable of tracking the desired values of the lateral position, velocity, and yaw angle. The Comparison between the proposed control system and two other studies in two different paths including lane-change and two-turn path close to the vehicle’s handling limit is carried out. Our proposed method shows more promising results in terms of root mean square of error criterion than the other two methods. In addition, the proposed controller is able to provide the actuator commands of each wheel properly, despite the parametric uncertainties.

Magnetic Shielding Implementation in the Small Satellite Reaction Wheel

Low Earth orbit satellites face challenges from Earth's magnetic field, causing attitude disturbances. Attaining a magnetic-dipole-free satellite is crucial. Layout optimization and in-orbit dipole compensation are common methods, but layout optimization can be impractical. In contrast, in-orbit dipole compensation struggles with rapidly changing magnetic dipoles like those from reaction wheel motors. This research proposes an alternative solution using Mu-metal, known for shielding against magnetic exposure. This shield can be applied to trap the magnetic field generated by the motors. Ground tests evaluated this approach. First, it determined the minimum distance between the magnetometer and the shield for accurate measurements with minimal interference, with the result of 10 cm as the least affected distance, particularly important for small satellite layout design. Second, it assessed the shield's effectiveness in trapping the motor-generated magnetic field. Tests showed a significant reduction in magnetic field magnitude and up to a 95% reduction in field fluctuations when the motor is activated. This research offers a practical solution for small satellite layout design, addressing the challenges posed by their compact dimensions. Mu-metal shielding proves effective for mitigating rapidly changing magnetic dipoles and enhancing magnetic cleanliness in low Earth orbit.

Optimization of the Semi-Active-Suspension Control of BP Neural Network PID Based on the Sparrow Search Algorithm.

Electric vehicles with hub motors have integrated the motor into the wheel, which increase the unsprung mass of the vehicle, and intensifies the vibration of the underspring components. The motor excitation during driving also intensifies the wheel vibration. The coupling effect between the two makes the performance of electric vehicles deteriorate. The article employed a disc-type permanent-magnet motor as the hub motor, taking into consideration the increase in sprung mass caused by the hub motor and the adverse effects of vertical vibration from motor excitation. Based on random road-surface excitation, and considering the secondary excitation caused by wheel motor drive and vehicle-road coupling, a coupled-dynamics model of a semi-active-suspension vehicle-road system for vertical vehicle motion is investigated under multiple excitations. Using body acceleration, suspension deflection, and dynamic tire load as evaluation indicators, a BP neural network PID controller based on the sparrow search algorithm optimization is proposed for the semi-active-suspension system. Compared with PID control and particle swarm optimization (PSO-BPNN-PID), the research findings indicate that the optimized semi-active suspension significantly improves the ride comfort of hub-motor electric vehicles, and meets the requirements for control performance under different vehicle driving conditions.

DEVELOPMENT OF AN ALL-TERRAIN CHASSIS WITH COMBINED THRUSTERS

Variants of propulsion systems for small-sized vehicles are considered; their advantages and disadvantages are noted. The modernize the all-terrain vehicle, a mover with motor wheels was taken, which has a small weigth and the least complexity of the design. The low weight of the motor wheels will significantly reduce the influence of dynamic loads on the elements of the propellers, which, in turn will significantly increase the life of the propeller. The absence of complex mechanisms in the design (transfer case, cardan gears and other rapidly wearing components) increases reliability and increases the durability of the all-terrain vehicle.

Development of control algorithm for autonomous intelligent robotic complex (AIRTC)

The work is dedicated to the development of a control algorithm for the autonomous intelligent robotic complex (AIRTC). The unmanned ground vehicle consists of a corpus that contains batteries, motor wheels, sensors, video cameras, on-board computer for processing data from sensors and video cameras. The general dimensions of the autonomous mobile robotic platform are 780x650x550 mm. The small size of the mobile platform allows it to be used in small areas, where the use of other vehicles is economically unprofitable. The key role in the autonomous mode of operation of the robotic complex is intended to the use of machine learning technologies to realize the possibility of performing the task assigned to the autonomous robotic platform in indoor and outdoor areas. An algorithm has been developed to control the basic platform of an autonomous robotic technical complex and to detect key obstacles automatically using a neural network. The accuracy of detecting the eight designated classes of obstacles was 85%.

Multi-objective liver cancer algorithm: A novel algorithm for solving engineering design problems

This research introduces the Multi-Objective Liver Cancer Algorithm (MOLCA), a novel approach inspired by the growth and proliferation patterns of liver tumors. MOLCA emulates the evolutionary tendencies of liver tumors, leveraging their expansion dynamics as a model for solving multi-objective optimization problems in engineering design. The algorithm uniquely combines genetic operators with the Random Opposition-Based Learning (ROBL) strategy, optimizing both local and global search capabilities. Further enhancement is achieved through the integration of elitist non-dominated sorting (NDS), information feedback mechanism (IFM) and Crowding Distance (CD) selection method, which collectively aim to efficiently identify the Pareto optimal front. The performance of MOLCA is rigorously assessed using a comprehensive set of standard multi-objective test benchmarks, including ZDT, DTLZ and various Constraint (CONSTR, TNK, SRN, BNH, OSY and KITA) and real-world engineering design problems like Brushless DC wheel motor, Safety isolating transformer, Helical spring, Two-bar truss and Welded beam. Its efficacy is benchmarked against prominent algorithms such as the non-dominated sorting grey wolf optimizer (NSGWO), multiobjective multi-verse optimization (MOMVO), non-dominated sorting genetic algorithm (NSGA-II), decomposition-based multiobjective evolutionary algorithm (MOEA/D) and multiobjective marine predator algorithm (MOMPA). Quantitative analysis is conducted using GD, IGD, SP, SD, HV and RT metrics to represent convergence and distribution, while qualitative aspects are presented through graphical representations of the Pareto fronts. The MOLCA source code is available at: https://github.com/kanak02/MOLCA.

Mathematical Model of Movement of a Mobile Robot with Omnidirectional Wheels

The article discusses the issue of controlling a four-wheeled mobile robot with omnidirectional wheelsof the mecanum type. An analysis of the rotational motion of the omnidirectional mecanum wheel was carriedout, based on its kinematics. For a specific robot with certain overall parameters, a graph of changes in the radiusof the mecanum wheel depending on the angle of its rotation was constructed. Kinematic and dynamic modelsof a mobile four-wheeled robot have been compiled, taking into account its geometric characteristics. The presented expressions are a mathematical description of the behavior of a mobile robot in statics and dynamics. Basedon the obtained models, the principles of operation of the motion control system for a four-wheeled mobile roboton omnidirectional wheels of the mecanum type are formed.

Impedance control for a Stewart‐structure‐based wheel‐legged robotic system in wheel motion

SummaryAn impedance control scheme is proposed for a Stewart‐structure‐based wheel‐legged robotic system to strengthen the dynamic attitude adjustment stability in wheel motion. The wheel‐leg, which is driven by electrical cylinders in the Stewart structure, is analyzed in kinematics and dynamics. The rotation in the axial direction of every electric cylinder is calculated to improve the accuracy of the kinematic model. To fulfill the impedance demands, a passive structure with 6 degrees of freedom (DOF) is modeled. The mass of the mechanism has a coupling effect on the impedance model for each DOF, which is a nonlinear function. As motion decoupling in the workspace has been completed for the Stewart structure, an impedance control strategy with inner‐loop position tracking is employed. An extended state observer (ESO) is designed to estimate the disturbances arising from the nonlinear coupling effects. Based on the ESO observation outputs, an active disturbance rejection control that explicitly handles the workspace limit is designed with guaranteed practical stability. By reducing force interaction and body vibration, the wheel‐legged robotic system keeps wheel motion stability on uneven roads. Multiple comparative experimental results are presented to validate the stability and effectiveness of the proposed method.

An Integrated Control Framework for Torque Vectoring and Active Suspension System

Four-wheel independently driven electric vehicles (FWID-EV) endow a flexible and scalable control framework to improve vehicle performance. This paper integrates the torque vectoring and active suspension system (ASS) to enhance the vehicle’s longitudinal and vertical motion control performance. While the nonlinear characteristic of the tire model leads to a relatively heavier computational burden. To facilitate the controller design and ease the load, a half-vehicle dynamics system is built and simplified to the linear-time-varying (LTV) model. Then a model predictive controller is developed by formulating the objective function by comprehensively considering the safety, energy-saving and comfort requirements. The in-wheel motor efficiency and the power loss of tire slip are treated as optimization indices in this work to reduce energy consumption. Finally, the effectiveness of the proposed controller is verified through the rapid-control-prototype (RCP) test. The results demonstrate the enhancement of the energy-saving as well as comfort on the basis of vehicle stability.

Modification of the In-Wheel Motor Housing and Its Effect on Temperature Reduction

This research proposes a novel cooling system to minimize the external rotor type of electric motor temperature by installing fan blades (wafters) on the inner housing of the electric motor. Fan blades (wafters) are made by printing using 3D printer technology and using polylactic acid (PLA) as the material. Wafters are then installed on an in-wheel motor with a power of 1500 W, having 48 poles and 52 slots. The study included thermal simulation and experimental techniques to ascertain how fan blades (wafters) affected the electric motor’s thermal properties. The motor rotated at 500 rpm during the experimental test with no load condition. The temperature of the electric motor is known using an infrared thermal imager. Using Ansys Motor-CAD 15.1 software, thermal modeling employs the lumped circuit model approach. Thermal simulation results show almost the same results as the experimental test results. Applying wafters on the in-wheel motor housing significantly reduces the winding temperature by 3.047 °C or experiences a temperature reduction of 4.34%. Using wafters in the in-wheel motor housing also speeds up the stable state temperature of the electric motor by 9 min compared to in-wheel motors without wafters.

Vibration Control of Car Body and Wheel Motions for In-Wheel Motor Vehicles Using Road Type Classification

In-wheel motor vehicles are gaining attention as a new type of electric vehicle due to their efficient power units located inside each wheel hub. However, they are more susceptible to wheel resonance due to the increase in unsprung mass caused by the weight of the motor. This can result in both decreased ride comfort and driving stability. To resolve this issue, in this study, we aim to apply an optimal switching controller with a semi-active actuator—a magnetorheological (MR) damper. For the implementation of the optimal switching controller, road type classification is also carried out. An acceleration sensor is used for the road type classification, and the control logics include a ride comfort controller (the linear quadratic regulator (LQR_Paved Road)) and a wheel motion controller (LQR_Off Road) for improved driving stability. For paved roads, the LQR_Paved Road control input is applied to the MR damper. However, if a road type prone to wheel resonance is detected, the control logic switches to the LQR_Off Road. During the transition, a weighted average of both the LQR_Paved Road and LQR_Off Road control input is applied to the actuator. Computer simulations are performed to evaluate the vibration control performance, including the ride comfort and driving stability on various road profiles.

Multi-objective optimization design of electric vehicle in-wheel motor based on Taguchi method

In order to solve the problem of motor performance degradation caused by torque ripple and large cogging torque of in-wheel permanent magnet synchronous motor for electric vehicles, Taguchi is used to optimize the magnetic pole of built-in Permanent magnet synchronous motor, and the orthogonal optimization matrix of magnetic pole parameters is established. Through the parameter optimization matrix, the workload of pole optimization is reduced and the optimization speed is improved. The optimization results show that the orthogonal matrix optimization can not only improve the output torque of permanent magnet synchronous motor, but also further control its torque ripple and cogging. The orthogonal matrix optimization method used in this paper for V-I type built-in permanent magnet synchronous motor has a certain positive significance, and provides a certain reference value for the subsequent motor performance optimization.

Design of Wheelchair Drive Unit Capable of Driving on Roads and Obstacles with Shape Conversion

Wheelchairs are widely used globally and are essential for providing autonomy and mobility to elderly and disabled people who have movement restrictions. Manual wheelchairs require operation through turning the wheels or pushing the wheelchair directly, thus posing mobility limitations for the user and caregiver. In contrast, electric wheelchairs, when used by the user, allow for improved flexibility by operating the wheelchair through a single control mechanism. However, the use of electric wheelchairs poses challenges in accessing areas with stairs and curbs, limiting the range of activity and thereby diminishing the quality of life for users and those reliant on electric wheelchairs. The electric wheelchair developed in this research incorporates a single motor for lightweight design. It uses a wheel travel variation actuator, eliminating the need for synchronization and allowing for low-power operation. This design reduces power loss from the caterpillar’s idling during wheel movement and includes the implementation of a pulley system. The optimal pulley belt length was calculated, and a deceleration device was installed inside the caterpillar, enabling a design that is compact, lightweight, and capable of high deceleration. On paved roads and flat terrain, the electric wheelchair is designed for high-speed travel using two pairs of front omni wheels and drive wheels. For terrains with stairs, speed bumps, unpaved roads, and unavoidable obstacles, the wheelchair is powered by caterpillars. The electric wheelchair developed through the research presented in this paper has verified the reliability of its transmission system through gear stress and deformation analysis. Additionally, an electric wheelchair based on the proposed concept was constructed to validate the drivability, safety, operability, and convenience of its driving unit. Furthermore, a user rode the constructed electric wheelchair to confirm that there were no issues with its drivability.

WAVE: Last Mile Delivery Robotic Platform With Stair-Climbing Ability Via Four-Bar Linkage-Based Locomotion

This article presents WAVE, a four-bar linkage-based stair-climbing robot. WAVE is designed to be a last mile delivery robot that can deliver goods on stairways and flat ground. When the cranks comprising WAVE undergo rotation, the body and legs rotate parallel to each other. The rotating body and legs climb the stairs alternately. WAVE has a right-angled groove tailored to the shape of the stairs at the bottom so that it can step stably on the stairs. To prevent the robot from tilting quickly when exiting the stairs, the groove was designed to divide the angle of the robot into three. In-wheel motors are attached to the bottom of the WAVE so that it moves using the wheels on flat ground. Also, as a result of the dynamic analysis, we obtained the motor torque and friction coefficient required to climb stairs. The length of the crank, which is a design variable, was determined via mechanical analysis. The first experiment was performed on the test bench to ensure that the WAVE worked as intended. In addition, through field tests, it was confirmed that WAVE can move upstairs and downstairs on stairs of various sizes.

Study of circular and rotational motion with the help of experimentation and mathematical modeling enhanced by digital technologies

Circular and rotational motion belongs to basic topics studied at upper secondary school and courses on Mechanics at University. Many studies show problems in understanding basic concepts related to kinematics and dynamics of these motions. In this paper we present a series of inquiry activities aimed at developing the understanding of these concepts and the laws of circular and rotating motion with the effective use of digital technologies. The activity on the videomeasurement of a uniform and decelerating bicycle wheel motion analyses the basic kinematic concepts. In the experiments carried out with the help of a centripetal force apparatus with the rotating system of carriages, the dynamics of circular motion can be investigated by observing and analysing the effect of various parameters on the centripetal force acting on the carriage. In addition to that, a mathematical model for decelerated motion of a bicycle wheel and a carriage can be designed. By manipulating and simulating the model for different parameters the best correspondence with experimental data can be found. The activities can be implemented at confirmation or guided inquiry level. Applying experimental as well as modelling approach to answer research questions students learn how science and physicists work.

A Direct Yaw Moment Control Framework Through Robust T-S Fuzzy Approach Considering Vehicle Stability Margin

The direct yaw moment control system of distributed drive electric vehicles provides a flexible control scheme to enhance the vehicle stability through four independently driven in-wheel motors. However, the vehicle nonlinearities may lead to the invalidation of control. To this end, a Takagi–Sugeno (T-S) fuzzy-based robust <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">H∞</i> control method is proposed to ensure the vehicle performance while addressing the nonlinear challenge. First, thanks to the T-S fuzzy modeling technology, the tire nonlinear characteristics are described by fuzzy rules, based on which the vehicle lateral dynamics model is established. Next, the safety region represented by the tire slip angles phase plane is presented to evaluate the vehicle stability performance. Considering the control priority of vehicle handling performance and stability control with different stability margins, a multiobjective optimization function is transformed into a standard robust performance optimization problem with dynamic weight coefficients. A T-S fuzzy-based robust <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">H∞</i> state feedback controller is then designed to ensure the system stability and <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">H∞</i> performance. Finally, the hardware-in-the-loop tests are conducted to validate the proposed controller. Comparative results show the effectiveness to improve the vehicle handling performance while ensuring the stability.

Path tracking fault-tolerant control of intelligent distributed drive electric vehicle based on sliding mode observer

In this paper, an intelligent distributed drive electric vehicle is used as the research object. The research aims to solve the problem of path-tracking control of intelligent vehicles when the single-side in-wheel motor of the front axle fails. A fault-tolerant control method based on sliding mode observer is proposed. Firstly, an overall vehicle dynamics model considering the failure factor is established, and the failure of the in-wheel motor is monitored by the sliding mode observer. Torque coordination compensation control is activated according to the observed failure. The control system mainly consists of two parts: the torque-coordinated lateral stability controller and the prediction fault tolerant deviation compensation controller. The torque-coordinated lateral stability controller controls the torque of the other wheels to balance the front wheel torque, and the prediction tolerant deviation compensation controller uses Model Predictive Control (MPC) to control the front wheel angle and rear wheel torque of the vehicle to reduce the lateral deviation. Finally, under double-lane change conditions, dynamics simulations and hardware-in-loop experiments are performed to validate the effectiveness of the proposed control method.

Vehicle pitch dynamics control using in-wheel motors

Implementation of in-wheel motors brings numerous advantages: decreased overall vehicle weight and manufacture cost, available accurate torque control for better road handling and powertrain high energy efficiency. Even so, when the motor is placed inside the wheel, the unsprung mass of the vehicle increases, leading to a less comfortable ride. This paper puts forward and studies a control system that takes advantage of the vertical component of the driving force provided by an in-wheel motor to enhance ride comfort and handling dynamics. The proportional integral (PI) controller was proposed to minimize the pitch acceleration response of the vehicle. Controller’s gains were optimized using the gradient descent method with sequential quadratic programing algorithm. A co-simulation approach and a dynamic model of the vehicle were presented. Data regarding the vehicle’s measurements was taken from a real car with in-wheel motors. The dynamic model of the car was validated based on the results derived during the road test experiment. Assessing the controller’s effectiveness, a co-simulation approach between the dynamic model and the control system was established. An acceleration test in a straight line showed a 25% increase in ride comfort as measured by the RMS pitch angular vibrations of the sprung mass. The control is attained with no increase in the tire load and the vehicle’s longitudinal dynamics.

State space model detection of driving fatigue considering individual differences and time cumulative effect

Fatigue is an important cause of traffic crashes, and effective fatigue detection models can reduce these crashes. Research has found large differences in fatigued driving performance from driver to driver, as well as a significant cumulative effect of fatigue on a given driver over time. Both sources of variation can decrease the accuracy of detection systems, but previous studies have not done enough to evaluate these differences. The purpose of this study is therefore to develop a fatigue detection model that considers individual differences and the time cumulative effect of fatigue. Data on the lateral position of the car in its lane, steering wheel movement, speed, and eye movement were collected from 22 drivers using a driving simulator with an eye-tracking system. Drivers’ subjective fatigue scores were collected using the Karolinska Sleepiness Scale. State space models (SSMs) were built to detect fatigue in each driver, considering his or her individual features. As a time series model, the SSM can also address the time cumulative effect of fatigue, and it does not require a large dataset to achieve high levels of accuracy. The differences in SSM results confirm that diversity does exist among drivers’ fatigued driving performance, so the ability of the SSM to take into account driver-specific information from each individual driver suggests that it is more suitable for fatigue detection than models that use aggregated driver data. Results show that the fatigue detection accuracy of the SSM (77.73%) is higher than that of artificial neural network models (61.37%). The advantages of accuracy, high interpretability, and flexibility make the SSM a comprehensive and valuable individualized fatigue detection model for commercial use.