Modeling and Control Strategies of the Thermal Management System for Electric Vehicles

电子设备和系统的热管理 控制(管理) 电动汽车 控制系统 计算机科学 热的 汽车工程 工程类 电气工程 机械工程 物理 人工智能 气象学 量子力学 功率(物理)
作者
Min Zhang,Liping Li,Jianhua Zhou,Yu Huang,Ran Zhen,Wen‐Bin Shangguan
出处
期刊:SAE technical paper series 卷期号:1
标识
DOI:10.4271/2025-01-8190
摘要

<div class="section abstract"><div class="htmlview paragraph">The electric vehicle thermal management system is a critical sub-systems of electric vehicles, and has a substantial impact on the driving range. The objective of this paper is to optimize the performance of the heat pump air conditioning system, battery, and motor thermal management system by adopting an integrated design. This approach is expected to effectively improve the COP (Coefficient of Performance) of cabin heating. An integrated thermal management system model of the heat pump air conditioning system, battery, and motor thermal management system is established using AMEsim. Key parameters, such as refrigerant temperature, pressure, and flow rate at the outlet of each component of the system are compared with the measured data to verify the correctness of the model established in this paper. Using the established model, the impact of compressor speed on the heating comfort of the cabin under high-temperature conditions in summer was studied, and a control strategy for rapid passenger compartment cooling is proposed. Additionally, a hybrid cooling strategy was established to address the priority issues of cabin and battery cooling, and compared with traditional cooling strategies in terms of cooling time and accuracy. The results demonstrate that the hybrid cooling strategy is capable of simultaneously cooling the cabin and battery if ambient temperature is 40°C. Compared with traditional methods that prioritize cooling either the cabin or the battery, the hybrid cooling strategy enables the rapid cooling of the battery while maintaining the cabin temperature comfort, and significantly reduces the discomfort time of passengers in the cabin by 64.25%.</div></div>
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
刚刚
渭阳野士完成签到,获得积分10
刚刚
2秒前
Auntiepress发布了新的文献求助10
2秒前
李爱国应助徐哈哈采纳,获得10
3秒前
www发布了新的文献求助10
3秒前
DW应助痕迹采纳,获得10
4秒前
ddd发布了新的文献求助10
5秒前
6秒前
6秒前
6秒前
DW应助江亭采纳,获得10
7秒前
慕青应助罗钦采纳,获得10
7秒前
初景应助Iridescend采纳,获得20
9秒前
9秒前
陶陶野畔发布了新的文献求助10
9秒前
12秒前
12秒前
缥缈的剑发布了新的文献求助10
12秒前
12秒前
美好绝施发布了新的文献求助10
12秒前
科研通AI6.4应助123采纳,获得10
13秒前
14秒前
15秒前
15秒前
16秒前
17秒前
17秒前
徐哈哈发布了新的文献求助10
18秒前
喔喔佳佳发布了新的文献求助10
20秒前
周不是舟发布了新的文献求助10
20秒前
哈哈哈发布了新的文献求助10
21秒前
22秒前
陈雨行发布了新的文献求助10
22秒前
ycg完成签到,获得积分10
23秒前
畅快枕头发布了新的文献求助10
24秒前
彭于晏应助缥缈的剑采纳,获得10
25秒前
molihuakai应助小巧的绿凝采纳,获得30
26秒前
科研通AI6.4应助李粉艳采纳,获得10
26秒前
星辰大海应助ercha采纳,获得10
26秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Principles of town planning: translating concepts to applications 1000
Management and the Arts 510
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
核安全综合知识2024版 500
Photothermal Science and Techniques 500
The Effective Clinical Neurologist 3ed 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7714475
求助须知:如何正确求助?哪些是违规求助? 9269787
关于积分的说明 20078765
捐赠科研通 7290854
什么是DOI,文献DOI怎么找? 3298178
关于科研通互助平台的介绍 2452416
邀请新用户注册赠送积分活动 2305538