Browse Topic: Optimization
The transportation industry is transforming with the integration of advanced data technologies, edge devices, and artificial intelligence (AI). Intelligent transportation systems (ITS) are pivotal in optimizing traffic flow and safety. Central to this are transportation management centers, which manage transportation systems, traffic flow, and incident responses. Leveraging Advanced Data Technologies for Smart Traffic Management explores emerging trends in transportation data, focusing on data collection, aggregation, and sharing. Effective data management, AI application, and secure data sharing are crucial for optimizing operations. Integrating edge devices with existing systems presents challenges impacting security, cost, and efficiency. Ultimately, AI in transportation offers significant opportunities to predict and manage traffic conditions. AI-driven tools analyze historical data and current conditions to forecast future events. The importance of multidisciplinary approaches and
Gear whine has emerged as a significant challenge for electric vehicles (EVs) in the absence of engine masking noise. The demand from customers for premium EVs with high speed and high torque density introduces additional NVH risks. Conventional gear design strategies to reduce the pitch-line velocity and increase contact ratio may impact EV torque capacitor or its efficiency. Furthermore, microgeometry optimization has limited design space to reduce gear noise over a wide range of torque loads. This paper presents a comprehensive investigation into the optimization of transfer gear blanks in a single-speed two-stage FDW electric drive unit (EDU) with the objective of reducing both mass and noise. A detailed multi-body dynamics (MBD) model is constructed for the entire EDU system using a finite-element-based time-domain solver. This investigation focuses on the analysis and optimization of asymmetric gear blank design features with three-slot patterns. A design-of-experiment (DOE
For electric vehicles, it is critical to develop drive units that produce a minimal amount of noise while meeting efficiency needs for a given application. Modern computational resources and accumulated experience allow for engineers to evaluate gear noise early in the development process and influence the design of the drive unit. This paper documents a high-fidelity virtual engineering approach to evaluate gear noise in a concept parallel axis drive unit and provide learnings to influence the design of external structures to improve NVH performance. By using the latest simulation tools to calculate and visualize the noise and vibration characteristics of the drive unit, designers and developers can implement design changes in optimization iterations to reduce noise and vibration. Gear harmonic response is firstly analyzed through a system model which considers structural deflection and misalignment, then a FE housing model is incorporated which is used for noise radiation evaluation
This study presents a novel methodology for optimizing the acoustic performance of rotating machinery by combining scattered 3D sound intensity data with numerical simulations. The method is demonstrated on the rear axle of a truck. Using Scan&Paint 3D, sound intensity data is rapidly acquired over a large spatial area with the assistance of a 3D sound intensity probe and infrared stereo camera. The experimental data is then integrated into far-field radiation simulations, enabling detailed analysis of the acoustic behavior and accurate predictions of far-field sound radiation. This hybrid approach offers a significant advantage for assessing complex acoustic sources, allowing for quick and reliable evaluation of noise mitigation solutions.
High-frequency whine noise in electric vehicles (EVs) is a significant issue that impacts customer perception and alters their overall view of the vehicle. This undesirable acoustic environment arises from the interaction between motor polar resonance and the resonance of the engine mount rubber. To address this challenge, the proposal introduces an innovative approach to predicting and tuning the frequency response by precisely adjusting the shape of rubber flaps, specifically their length and width. The approach includes the cumulation of two solutions: a precise adjustment of rubber flap dimensions and the integration of ML. The ML model is trained on historical data, derived from a mixture of physical testing conducted over the years and CAE simulations, to predict the effects of different flap dimensions on frequency response, providing a data-driven basis for optimization. This predictive capability is further enhanced by a Python program that automates the optimization of flap
This study focuses on the numerical analysis of weather-strip contact sealing performance with a variable cross-sectional design, addressing both static and dynamic behaviors, including the critical issue of stick-slip phenomena. By employing finite element modeling (FEM), the research simulates contact pressures and deformations under varying compression loads, DCE (Door Closing Efforts) requirements, typical in automotive applications. The analysis evaluates how changes in the cross-sectional shape of the weather-strip affect its ability to maintain a consistent sealing performance, especially under dynamic vehicle operations. The study also delves into stick-slip behavior, a known cause of noise and vibration issues, particularly improper/ loosened door-seal contact during dynamic driving condition. This study identifies key parameters influencing stick-slip events, such as friction coefficients, material stiffness, surface interactions, sliding velocity, wet/dry condition
Topology optimization (TO) in electrochemical systems has recently attracted many researchers. Previous studies suggested minimal performance differences between 2D and 3D designs, indicating that 2D models suffice to enhance performance, especially in unidirectional flow scenarios. A later study found that the concentration distribution in an optimized 2D flow system differed from that in a unidirectional flow system. We posited that pulsating flow could further enhance the performance of such systems. First, we initiated TO for a diffusion-reaction system in a steady state. The optimized structure obtained from this process served as the foundation for subsequent investigations involving a pulsating flow source in convection-diffusion-reaction systems. We introduced two different systems with distinct flow natures: one characterized by a flow nature of 1D and the other by a flow nature of 2D. The results demonstrated that the optimized structure with a heterogeneous distribution
The integrated bracket is a plastic part that packages functional components such as the ADAS (Advanced Driver Assistance System) camera, rain light sensor, and the mounting provisions of the auto-dimming IRVM (Inner Rear View Mirror). This part is fixed on the windshield of an automobile using double-sided adhesive tapes and glue. ADAS, rain light sensors, and auto-dimming IRVM play an important part in the safety of the driver and everyone present in the automobile. This makes proper functioning of the integrated bracket very integral to occupant safety. Prior to this work, the following literature; Integrated Bracket for Rain Light Sensor/ADAS/Auto-Dimming IRVM with provision of mounting for Aesthetic Cover [1] outlines the design considerations and advantages of mounting several components on the same bracket. It follows the theme where the authors first define the components packaged on the integrated bracket and then the advantages of packaging multiple components on a single
Items per page:
50
1 – 50 of 7027