Browse Topic: Computer simulation

Items (3,327)
ABSTRACT A simulation capable of modeling grid-tied electrical systems, vehicle-to-grid (V2G) and vehicle-to-vehicle(V2V) resource sharing was developed within the MATLAB/Simulink environment. Using the steady state admittance matrix approach, the unknown currents and voltages within the network are determined at each time step. This eliminates the need for states associated with the distributed system. Each vehicle has two dynamic states: (1) stored energy and (2) fuel consumed while the generators have only a single fuel consumed state. One of its potential uses is to assess the sensitivity of fuel consumption with respect to the control system parameters used to maintain a vehicle-centric bus voltage under dynamic loading conditions.
Jane, Robert S.Parker, Gordon G.Weaver, Wayne W.Goldsmith, Steven Y.
Abstract Test cycle simulation is an essential part of the vehicle-in-the-loop test, and the deep reinforcement learning algorithm model is able to accurately control the drastic change of speed during the simulated vehicle driving process. In order to conduct a simulated cycle test of the vehicle, a vehicle model including driver, battery, motor, transmission system, and vehicle dynamics is established in MATLAB/Simulink. Additionally, a bench load simulation system based on the speed-tracking algorithm of the forward model is established. Taking the driver model action as input and the vehicle gas/brake pedal opening as the action space, the deep deterministic policy gradient (DDPG) algorithm is used to update the entire model. This process yields the dynamic response of the output end of the bench model, ultimately producing the optimal intelligent driver model to simulate the vehicle’s completion of the World Light Vehicle Test Cycle (WLTC) on the bench. The results indicate that
Gong, XiaohaoLi, XuHu, XiongLi, Wenli
The hippocampus plays a crucial role in brain function and is one of the important areas of concern in closed head injury. Hippocampal injury is related to a variety of factors including the strength of mechanical load, animal age, and helmet material. To investigate the order of these factors on hippocampal injury, a three-factor, three-level experimental protocol was established using the L(3) orthogonal table. A closed head injury experiment regarding impact strength (0.3MPa, 0.5MPa, 0.7MPa), rat age (eight- week-old, ten-week-old, twelve-week-old), and helmet material (steel, plastic, rubber) were achieved by striking the rat's head with a pneumatic-driven impactor. The number of hippocampal CA3 cells was used as an evaluation indicator. The contribution of factors to the indicators and the confidence level were obtained by analysis of variance. The results showed that impact strength was the main factor affecting hippocampal injury (contribution of 89.2%, confidence level 0.01
Wang, PengSong, XueweiZhu, XiyanQiu, JinlongYang, ShuaijunZhao, Hui
Abstract Enhancing the performance of a ride-oriented algorithm to provide ride comfort and vehicle stability throughout different terrains is a challenging task. This article aims to improve the performance of the state-of-the-art continuous skyhook algorithm in coupled motion modes with an optimally tuned stability augmentation system (SAS). The tuning process is carried out using a chaotic map-initialized particle swarm optimization (C-PSO) approach with ride comfort and roll stability as a performance index. A large van model built-in CarSim is co-simulated with a C-PSO algorithm and control system designed in MATLAB. To realize the feasibility and effectiveness of the proposed system, a software-in-loop test is conducted on five complex ride terrains with different dominant vehicle body motion modes. The test results are compared against the passive system, four corner continuous skyhook control, and four corner type-1 fuzzy control. The test results confirm the effectiveness of
Rajasekharan Unnithan, Anand RajSubramaniam, Senthilkumar
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