Browse Topic: Motor-in-wheel drives
Letter from the Guest Editors
The multi-articulated vehicle uses distributed drive mode. Due to its large degree of freedom of movement and the large number of driving shafts, different torque distribution methods affect the operational stability of the vehicle, how to coordinate and distribute the torque of each driving motor has become an urgent problem to be solved. To improve drive stability of the multi-articulated vehicles, propose a layered torque allocation control strategy. The upper-layer sliding mode controller determines the required additional yaw moments of each car body based on the linear reference model, the controller is characterized by swift response and a strong ability to resist interference. The lower-level allocation module comprehensively considers the torque output limitations of the electric hub motors, the prevailing road adhesion state, and the corrective yaw moment constraints given by the upper layer, and constructs an optimization objective function centered on the uniformity and stability of tire load. The optimal distribution of driving forces for each wheel is completed by solving this function dynamically. To validate the strategy's effectiveness, a vehicle dynamics model is built in the multi-body dynamics software ADAMS/View. Using a joint simulation framework integrating ADAMS/View and MATLAB®/Simulink, the effect of the layered control strategy is evaluated in comparative simulation with uncontrolled situation under U-turn and single lane change conditions. The simulation outcomes demonstrate that, compared to uncontrolled situation, the yaw rate deviation of each car body under the torque layered control are significantly reduced, and the adhesion utilization rate of tire is also effectively controlled, thereby the driving stability is improved.
The transition to software-defined vehicles (SDVs) necessitates a paradigm shift in both control strategies and vehicle architecture. The EU-funded R&D project SmartCorners addresses this challenge by developing integrated, modular, and scalable smart corner systems (SCS) that combine in-wheel motor (IWM)-based propulsion, brake blending, active suspension system, and steer-by-wire functionality in one module. These SCS can be retrofit or smoothly integrated into the highly adaptable skateboard chassis architecture of modern electric vehicles (EVs), enabling scalable deployment across diverse vehicle types. The central approach of this paper is the utilization of artificial intelligence (AI) and machine learning (ML) to implement multi-layer, data-driven control strategies, facilitating real-time actuation, fault mitigation, and user-centric EV architecture. The SmartCorners project strives to demonstrate significant enhancements, including improved real-world driving range due to enhanced energy-efficiency, reduced component and system costs, and a cut-down in development time of EVs, enabled by digital-twin-based design methodologies. Beyond these performance gains, SmartCorners establishes the foundational principles of modularity, adaptability, and software integration that underpin the evolution toward SDVs. The role of thermal and cabin comfort control is completely different for EVs and internal combustion engine vehicles, with the latter using waste heat from the combustion of fossil fuels for cabin heating, ventilation, and cooling (HVAC). In EVs the required energy is directly taken from the traction battery and precise thermal and cabin comfort control affecting essential components of the vehicle but also the user-perceived driving experience. These project achievements highlight a critical bridge between innovation and electrification on component-level, and the holistic software-defined mobility systems of the future.
Performing transportation and exploration tasks on rugged terrain requires both high load-bearing capacity and large suspension stroke. However, the corner module configurations applied to challenging terrain have rarely been explored. This article proposes an integrated framework that combines bionic principles with topology graph–based type synthesis. This framework leads to the creation of a reconfigurable wheel-legged mechanism capable of switching between wheeled locomotion and legged gait modes, which is then implemented as a corner module system. First, inspired by the skeletal–muscular system of the equine leg, a structure–function mapping relationship between the biological system and the mechanical system is established. Second, a multi-loop closed-chain mechanism with biomimetic morphology is represented in the form of graph theory. A configuration atlas of the wheel-legged hybrid mechanism is generated based on the contracted graph and open-loop kinematic chains, and configuration optimization is carried out. Third, on the basis of the optimized configuration, a biomimetic vibration isolation system is integrated. Finally, a corner module system that integrates the reconfigurable wheel-legged mechanism with steering, hub motor is designed, as well as the mechanical structure of modular transporters based on the aforementioned corner modular architecture. The vibration reduction performance and various locomotion modes of the modular transporter are verified by multibody dynamic simulation.
Vehicle electrification has introduced new powertrain possibilities, such as the use of four independent in-wheel motors, enabling the development of control strategies that enhance vehicle safety and drivability. The development of a model capable of simulating vehicle behavior is fundamental for control system design. A high-fidelity model takes into account several parameters, such as vehicle ride height, track width, wheelbase, and others, making it possible to evaluate the vehicle’s behavior and allowing for prior validation of the design, thus contributing to improved vehicle safety and performance. In this context, this study presents a lateral dynamic model of a Formula 4WD vehicle with in-wheel motors, enabling the simulation and analysis of the vehicle’s behavior in cornering maneuvers. To achieve this, the complete lateral model is developed using MATLAB Simulink as the platform, incorporating the semi-empirical Hans Pacejka tire model, calculating yaw moment, and analyzing forces to accurately describe the vehicle’s dynamics.
A design is presented for an electro-mechanical switchgear, intended for reconfiguring the windings of an electric machine whilst in operation. Specifically, the design is developed for integration onto an in-wheel automotive motor. The motor features 6 phase fractions, which can be reconfigured by the switchgear between series-star or parallel-star arrangements, thereby doubling the torque or speed range of the electric machine. The switchgear has a mass of only 1.8kg – around one tenth of the equivalent 2-speed transmission which might otherwise be employed to achieve a similar effect. As well as the extended operating envelope, the reconfigurable winding motor offers benefits in efficiency and power density. The mechanical solution presented is expected to achieve efficiency and cost advantages over equivalent semiconductor-based solutions, which are practical barriers to adoption in automotive applications. The design uses only mechanical contacts and a single actuator, thereby offering a convincing techno-economic proposition. Furthermore, it is shown that a torque interruption time of <30ms is feasible for reconfiguration events using the mechanical relay; whilst this is longer than for a semiconductor-based solution, it is likely to be imperceptible to vehicle passengers and not affect the driver experience. The project outcomes show that mechanical relay designs can in fact provide a competitive all-round solution for this functionality, making reconfigurable motors a realistic prospect for automotive applications.
In highly populated countries two-wheelers are the most convenient mode of transportation. But at the same time, these vehicles consume more fuel and produces emissions in urban driving. This work is aimed at developing a hybrid two-wheeler for reducing fuel consumption and emissions by incorporating electric vehicle technology in a conventional two-wheeler. The hybrid electric scooter (HES) made consisted of an electric hub motor in the front wheel as the prime mover for the electrical system. The powertrain of the HES was built using a parallel hybrid structure. The electric system is engaged during startup, low speeds, and idling, with a simple switch facilitating the transition between electric and fuel systems. The HES was fabricated and tested through trial runs in various operating modes. Before conversion to a hybrid system, the two-wheeler achieved a mileage of 34 km/liter. After conversion, the combined power sources resulted in an overall mileage of 55 km. It was observed that the voltage supplied to the motor increases proportionally with speed. The HES model was developed using MATLAB-Simulink, and simulation results indicated that the vehicle operates in electric mode at speeds below 20 km/h and switches to an internal combustion engine above 20 km/h. Operating the HES in electric mode at speeds below 20 km/h can significantly reduce fuel consumption and emissions, making it an ideal solution for urban driving in densely populated areas.
When riding an e-bike, riders are faced with the question of whether there is enough energy left in the battery to reach the destination with the desired level of support. Therefore, e-bike riders have range anxiety. Specifically, this describes the fear that the battery charge will be exhausted before there is an opportunity to recharge it and that it will no longer be possible to use the electric support. However, e-bike riders have so far had to decide for themselves whether the available battery charge is sufficient for riding the planned route or whether the desired destination can be reached. In this context, the challenge is to decide how much electric propulsion support can be used so that an appropriate amount of effort can be achieved for the entire ride. In order to assist e-bike riders with this problem, the objective of this paper is to present an approach towards a system that provides rider-adaptive support over the entire ride of a defined route. This involves using the propulsion support in such a way that the rider requires an appropriate level of effort. The rider-adaptive support is to be implemented via an automatic mode of the e-bike propulsion system, which automatically sets the corresponding support intensity. The assistance system is designed to ensure that a planned destination can be reached using the rider-adaptive support. To achieve this, the use of the propulsion support is optimized and automatically adjusted according to the available energy and the route to be cycled. The implementation will be carried out as a predictive energy management system. This calculates an optimized support strategy based on an energy demand prediction for the route to be cycled and the available energy of the e-bike battery.
Hyundai Motor Group's visual design team has been on a roll in creating unusual and attractive passenger vehicles. Now, the automaker's engineering team has come up with its own unique creation: the Universal Wheel Drive System. The Uni Wheel is a significant development for both Hyundai Motor Company and the Kia Corporation, which jointly unveiled the device at a “Uni Wheel Tech Day” in Seoul, South Korea, in November. The Uni Wheel is not a hub motor, but it does move some of the main drive system components to the available room inside the wheel hub.
Items per page:
50
1 – 50 of 65