Browse Topic: Energy conservation
This study introduces a computational approach to evaluate potential noise issues arising from liftgate gaps and their contribution to cabin noise early in the design process. This computational approach uses an extensively-validated Lattice Boltzmann method (LBM) based computational fluid dynamics (CFD) solver to predict the transient flow field and exterior noise sources. Transmission of these noise sources through glass panels and seals were done by a well-validated statistical energy analysis (SEA) solver. Various sealing strategies were investigated to reduce interior noise levels attributed to these gaps, aiming to enhance wind noise performance. The findings emphasize the importance of integrating computational tools in the early design stages to mitigate wind noise issues and optimize sealing strategies effectively.
Artificial intelligence (AI) systems promise transformative advancements, yet their growth has been limited by energy inefficiencies and bottlenecks in data transfer. Researchers at Columbia Engineering have unveiled a groundbreaking solution: a 3D photonic-electronic platform that achieves unprecedented energy efficiency and bandwidth density, paving the way for next-generation AI hardware.
E-mobility is revolutionizing the automotive industry by improving energy-efficiency, lowering CO2 and non-exhaust emissions, innovating driving and propulsion technologies, redefining the hardware-software-ratio in the vehicle development, facilitating new business models, and transforming the market circumstances for electric vehicles (EVs) in passenger mobility and freight transportation. Ongoing R&D action is leading to an uptake of affordable and more energy-efficient EVs for the public at large through the development of innovative and user-centric solutions, optimized system concepts and components sizing, and increased passenger safety. Moreover, technological EV optimizations and investigations on thermal and energy management systems as well as the modularization of multiple EV functionalities result in driving range maximization, driving comfort improvement, and greater user-centricity. This paper presents the latest advancements of multiple EU-funded research projects under
Technological advances have led to the widespread use of electric devices and vehicles. These innovations are not only convenient but also environmentally friendly, offering an alternative to polluting fuel-driven machines. Lithium-ion batteries (LIBs) are widely used in electrical appliances and vehicles. Commercial LIBs comprise an organic electrolyte solution, which is considered indispensable to make them energy efficient. However, ensuring safety becomes a concern and may be difficult to achieve with the rising market demand.
In traffic scenarios, the spacing between vehicles plays a key role, as the actions of one vehicle can significantly impact others, particularly with regards to energy conservation. Accordingly, modern vehicles are equipped with inter-vehicle communication systems to maintain specific distances between vehicles. The aerodynamic forces experienced by both leading vehicles (leaders) and following vehicles (followers) are connected to the flow patterns in the wake region of the leaders. Therefore, improving our understanding of the turbulent characteristics associated with vehicles platooning is important. This paper investigates the effects of inter-vehicle distances on the flow structure of two vehicles: a small SUV as the leader and a larger light commercial van as the follower, using a Delayed Detached Eddy Simulation (DDES) CFD technique. The study focuses on three specific inter-vehicle distances: S = 0.28 L, 0.4L, and 0.5L, where S represents the spacing between the two vehicles
As automotive technology advances, the need for comprehensive environmental awareness becomes increasingly critical for vehicle safety and efficiency. This study introduces a novel integrated wind, weather, and motion sensor designed for moving objects, with a focus on automotive applications. The sensor’s potential to enhance vehicle performance by providing real-time data on local atmospheric conditions is investigated. The research employs a combination of sensor design, vehicle integration, and field-testing methodologies. Findings prove the sensor’s capability to accurately capture dynamic environmental parameters, including wind speed and direction, temperature, and humidity. The integration of this sensor system shows promise in improving vehicle stability, optimizing fuel efficiency through adaptive aerodynamics, and enhancing the performance of autonomous driving systems. Furthermore, the study explores the potential of this technology in contributing to connected vehicle
In addition to electric vehicles (EVs), hydrogen fuel cell systems are gaining attention as energy-efficient propulsion options. However, designing fuel cell vehicles presents unique challenges, particularly in terms of storage systems for heavy hydrogen tanks. These challenges impact factors such as NVH (noise, vibration, and harshness) and safety performance. This study presents a topology optimization study for Hydrogen Energy Storage System (HESS) tank structure in Class 5 trucks, with a focus on enhancing the modal frequencies. The study considers a specific truck configuration with a HESS structure located behind the crew cab, consisting of two horizontally stacked hydrogen tanks and two tanks attached on both sides of the frame. The optimization process aimed to meet the modal targets of this hydrogen tank structure in the fore-aft (X) and lateral (Y) directions, while considering other load cases such as a simplified representation of GST (global static torsion), simplified
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