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 量子力学 气象学 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>

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

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
甜甜麦片发布了新的文献求助10
刚刚
酷炫的不言完成签到,获得积分20
刚刚
刚刚
李爱国应助大头头很大采纳,获得30
1秒前
杨鑫瑞发布了新的文献求助10
1秒前
YingxueRen完成签到,获得积分10
1秒前
2秒前
2秒前
2秒前
今后应助Eva采纳,获得10
2秒前
3秒前
susan完成签到,获得积分10
3秒前
puchang007发布了新的文献求助10
3秒前
4秒前
婕婕婕发布了新的文献求助30
5秒前
活泼平凡完成签到,获得积分10
5秒前
研途发布了新的文献求助10
5秒前
5秒前
Akim应助希音采纳,获得10
6秒前
彦卿发布了新的文献求助10
6秒前
Rasay完成签到,获得积分10
6秒前
辛勤的日记本完成签到,获得积分10
7秒前
gaoyunfeng发布了新的文献求助10
8秒前
伶俐断天发布了新的文献求助10
9秒前
9秒前
头发茂密的我完成签到,获得积分10
10秒前
aoi发布了新的文献求助10
10秒前
10秒前
勤奋冷之发布了新的文献求助10
11秒前
12秒前
Eva完成签到,获得积分10
12秒前
wqk发布了新的文献求助150
14秒前
FashionBoy应助mdjinij采纳,获得10
14秒前
gaoyunfeng完成签到,获得积分10
14秒前
1renebaebae完成签到,获得积分20
15秒前
15秒前
量子星尘发布了新的文献求助10
16秒前
果粒陈完成签到,获得积分10
16秒前
16秒前
Eva发布了新的文献求助10
17秒前
高分求助中
Comprehensive Toxicology Fourth Edition 24000
(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
Pipeline and riser loss of containment 2001 - 2020 (PARLOC 2020) 1000
World Nuclear Fuel Report: Global Scenarios for Demand and Supply Availability 2025-2040 800
Handbook of Social and Emotional Learning 800
Risankizumab Versus Ustekinumab For Patients with Moderate to Severe Crohn's Disease: Results from the Phase 3B SEQUENCE Study 600
Lloyd's Register of Shipping's Approach to the Control of Incidents of Brittle Fracture in Ship Structures 500
热门求助领域 (近24小时)
化学 医学 生物 材料科学 工程类 有机化学 内科学 生物化学 物理 计算机科学 纳米技术 遗传学 基因 复合材料 化学工程 物理化学 病理 催化作用 免疫学 量子力学
热门帖子
关注 科研通微信公众号,转发送积分 5143039
求助须知:如何正确求助?哪些是违规求助? 4341079
关于积分的说明 13519541
捐赠科研通 4181353
什么是DOI,文献DOI怎么找? 2292877
邀请新用户注册赠送积分活动 1293512
关于科研通互助平台的介绍 1236099