Browse Topic: Vehicle drive systems
Customers are expecting higher level of refinement in electric vehicle. Since the background noise is less in electric vehicle in comparison with ICE, it is challenging for NVH engineers to address even minor noise concerns without cost and mass addition. Higher boom noise is perceived in the test vehicle when driven on the coarse road at a speed of 50 kmph. The test vehicle is rear wheel driven vehicle powered by electric motor. Multi reference Transfer Path Analysis (TPA) is conducted on the vehicle to identify the path through which maximum forces are entering the body. Based on the findings from TPA, solutions like reduction in the dynamic stiffness of the suspension bushes are optimized which resulted in reduction of noise. To reduce the noise further, Operational Deflection Shape (ODS) analysis is conducted on the entire vehicle to identify the deflection shapes of all the suspension components and all the body panels like floor, roof, tailgate, dash panel, quarter panel and
In Electric vehicle Drive Unit Gears, high mesh misalignments result in shift in load distribution of a gear pair that can increase contact and bending stresses. It can move the peak bending and contact stresses to the edge of the face width and increase gear noise as well. Lower misalignment value is often required to reduce the peak bending and contact stresses and have a balanced load distribution along the gear flank, which in turn helps in reducing noise and improving durability of drive unit. This paper delineates Prescriptive Analytics method that combines virtual simulations, Machine learning (ML) and optimization techniques to minimize different gear misalignments for the electric vehicle drive units. Generally, the manual optimization process is carried out by sequential modifications of stiffness of individual components. However, this process is time consuming and does not account for interactions between the components. In this study, firstly, Machine learning models are
The inductance parameter is important for the flux regulation performance of the hybrid excitation motor, and the axial structure leads to the change in the inductance parameter of the axial-radial hybrid excitation motor (ARHEM). To clarify the inductance characteristic of the ARHEM with different winding construction and the mutual coupling effect between the axial excitation and permanent magnet excitation on the inductance. Firstly, the structure of the ARHEM is presented. Secondly, the self and mutual inductance characteristics of ARHEM are analyzed using the winding function method. Then, the influence of the axial excitation structure on the armature reaction field and saliency ratio of ARHEM. On this basis, the mechanism of the mutual coupling, between the axial excitation and permanent magnet field under different excitation currents on the main air gap magnetic field, and the inductance of ARHEM with fractional slot are revealed.
Design validation plays a crucial role in the overall cost and time allocation for product development. This is especially evident in high-value manufacturing sectors like commercial vehicle electric drive systems or e-axles, where the expenses related to sample procurement, testing complexity, and diverse requirements are significant. Validation methodologies are continuously evolving to encompass new technologies, yet they must be rigorously evaluated to identify potential efficiencies and enhance the overall value of validation tests. Simulation tools have made substantial advancements and are now widely utilized in the development phase. The integration of simulation-based or simulation-supported validation processes can streamline testing timelines and sample quantities, all the while upholding quality standards and minimizing risks when compared to traditional methods. This study examines various scenarios where the implementation of advanced techniques has led to a reduction in
This project presents the development of an advanced Autonomous Mobile Robot (AMR) designed to autonomously lift and maneuver four-wheel drive vehicles into parking spaces without human intervention. By leveraging cutting-edge camera and sensor technologies, the AMR integrates LIDAR for precise distance measurements and obstacle detection, high-resolution cameras for capturing detailed images of the parking environment, and object recognition algorithms for accurately identifying and selecting available parking spaces. These integrated technologies enable the AMR to navigate complex parking lots, optimize space utilization, and provide seamless automated parking. The AMR autonomously detects free parking spaces, lifts the vehicle, and parks it with high precision, making the entire parking process autonomous and highly efficient. This project pushes the boundaries of autonomous vehicle technology, aiming to contribute significantly to smarter and more efficient urban mobility systems.
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
In conventional vehicles the shift strategy has a well-known impact on the system’s efficiency. An appropriate gear choice allows the internal combustion engine (ICE) to operate in efficient operating points (OPs) and thus contributes significantly to a reduced fuel consumption. Further efficiency improvements can be achieved by the hybridization of the powertrain. Due to the two propulsion systems, an additional degree of freedom arises, that requires an energy management strategy (EMS). The EMS controls the split of the requested power between the electric machine (EM) and the ICE. Accordingly, the system’s overall efficiency in hybrid electric vehicles (HEVs) is highly influenced by the quality of the EMS. This paper proposes to adapt an existing method for deriving fuel-optimal rule-based EMS by including the shift strategy for parallel HEVs. It is shown that fuel-optimal control can be achieved. The analytically derived look-up tables can be used to automatically calibrate in
This SAE Standard is applicable to snowmobiles as defined in SAE J33.
Toyota, Mazda and Subaru announced a new technological effort to create new internal combustion engines and ways to use them in the electrification era, specifically for hybrid and plug-in hybrid vehicles. The companies said at a joint press conference in Japan that they would encourage increased use of petroleum alternatives like biofuels and eFuels in their effort to create carbon-neutral vehicles. A joint statement from the three OEMs claims this push for new and better ICEs comes with a focus on “carbon as the enemy” as they develop engines that can better work with electric motors, batteries, and other electric drive units. Toyota, Mazda and Subaru made clear they are not getting rid of EV-only vehicle plans. Here's how each company will approach the new ICE+EV era (quotes provided in English by on-site interpreters).
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