基于迭代动态规划的动力电池组热管理优化策略

doi:10.19562/j.chinasae.qcgc.2022.05.008

摘要/Abstract

摘要：

动力电池在电动汽车行驶过程中不断产热，持续高温会降低电池的使用寿命，危害汽车的运行安全。因此，采取高效、节能的冷却优化策略，提高动力电池工作效率十分必要。本文基于电池的生热特性和牛顿冷却定律建立电池组集中质量热模型，并与AMESim中建立的电池液冷系统模型进行对比，验证其准确性。针对电池热管理系统的高度非线性与时变性，提出一种在多维搜索空间迭代逼近最优值的迭代动态规划（IDP）策略。通过MatLab-AMESim联合仿真对比，证明了此方法以最小的能耗对电池组温度进行快速冷却，且冷却液流速稳定，验证了IDP优化策略的高效性与节能性。

关键词: 锂离子电池组, 迭代动态规划, 集中热模型, 液冷系统, 电池热管理

Abstract:

During the driving of electric vehicles， the power battery continuously generates heat. Continuous high temperature will affect the battery life and the safety of the operation of electric vehicles. Therefore， it is necessary to adopt an efficient and energy-saving cooling optimization strategy in order to improve the efficiency of the power battery. Based on the heat generation characteristics of battery and Newton's law of cooling， a concentrated mass heat model of the battery pack is established in this paper， and compared with the battery liquid cooling model set up in AMESim to verify the accuracy of the model. In view of the high nonlinearity and time varying of the battery thermal management system， an iterative dynamic programming （IDP） strategy of iterative approximation of optimal control in multidimensional search space is proposed in this paper. Through the co-simulation of Matlab-AMESim， it shows that the proposed IDP optimization strategy can rapidly cool the temperature of the battery pack with minimum energy consumption， and the coolant flow rate is stable， which verifies the high efficiency and energy saving of the optimization strategy.

Key words: lithium-ion battery pack, iterative dynamic programming, concentrated heat model, liquid cooling system, battery thermal management

马彦,李佳怡,马乾,陈明超. 基于迭代动态规划的动力电池组热管理优化策略[J]. 汽车工程, 2022, 44(5): 709-721.

Yan Ma,Jiayi Li,Qian Ma,Mingchao Chen. Optimization Strategy of Thermal Management of Power Battery Pack Based on Iterative Dynamic Programming[J]. Automotive Engineering, 2022, 44(5): 709-721.

图/表 20

图1

图2

表1

AMESim 模型与冷却液物理参数"

参数	数值	参数	数值
$A / m 2$	$5.3 × 10 - 3$	$ρ / (k g · m - 3)$	1 071
$c b / (J · k g - 1 · K - 1)$	1 120.97	$P r$	25.825
$m b / g$	73	$c f / (J · k g - 1 · K - 1)$	3 297
$d / m m$	18	$λ$	0.42

表1

图3

图4

图5

图6

图7

图8

图9

图10

表2

恒流3C温度曲线的响应参数"

算法	$T 1 / K$	$T 7 / K$	$E s s 1 / K$	$E s s 7 / K$	$T s / s$
PID	302.44	302.92	0.56	0.08	164
DP	302.39	302.92	0.51	0.08	80
IDP	302.64	303.23	0.36	0.23	72

表2

图11

图12

表3

U_N_U工况温度曲线的响应参数"

算法	$T 1 / K$	$T 7 / K$	$E s s 1 / K$	$E s s 7 / K$	$E s s m a x$	$T s / s$	$σ / %$
PID	302.79	302.64	0.21	0.64	2.66	124	0.88
DP	302.28	302.76	0.72	0.24	1.31	77	0.43
IDP	302.62	303.34	0.38	0.34	1.26	55	0.41

表3

图13

图14

图15

图16

图17

参考文献 53

1	WANG Z， DU C. A comprehensive review on thermal management systems for power lithium-ion batteries ［J］. Renewable and Sustainable Energy Reviews， 2021， 139：110685.
2	戴海燕，王玉兴.基于电化学热耦合模型的电动汽车电池模组热特性研究［J］.汽车工程，2020，42 （5）：665-671.
	DAI H Y， WANG Y X. Study on thermal characteristics of battery modules of electric vehicle based on electrochemical thermal coupling model［J］. Automotive Engineering， 2020，42 （5）：665-671.
3	李文策，白雪，齐亮，等.新能源汽车时代新征程：2017回顾及未来展望［J］.北京理工大学学报（社会科学版）， 2018，20（2）：1-7.
	LI W C， BAI X， QI L， et al. New energy vehicle new era and new expedition：2017 review and future outlooks［J］. Journal of Beijing Institute of Technology（Social Science Edition）， 2018，20（2）：1-7.
4	CABEZA L， FRAZZICA A， CHÀFER M， et al. Research trends and perspectives of thermal management of electric batteries： Bibliometric analysis ［J］. Journal of Energy Storage，2020，32： 101976.
5	盘朝奉，刘兵，陈龙，等.锂离子电池温升特性分析及液冷结构设计［J］.西南交通大学学报， 2020，55（1）：68-75.
	PAN C F， LIU B， CHEN L， et al. Temperature rise characteristic analysis and liquid cooling structure design of lithium battery［J］. Journal of South Jiao Tong University. 2020，55（1）：68-75.
6	JORIS J， JOERI V. A comprehensive review of future thermal management systems for battery-electrified vehicles［J］. Journal of Energy Storage， 2020，31：101551.
7	PARK S， AHN C. Computationally efficient stochastic model predictive controller for battery thermal management of electric vehicle［J］. IEEE Transactions on Vehicular Technology，2020，69（8）：8407-8419.
8	GERMAN R， SHILI S， DESREVEAUX A， et al. Dynamical coupling of a battery electro-thermal model and the traction model of an EV for driving range simulation［J］. IEEE Transactions on Vehicular Technology， 2019，69（1）：328-337.
9	HORREIN L， BOUSCAYROL A， CHENG Y， et al. Influence of the heating system on the fuel consumption of a hybrid electric vehicle［J］. Energy Conversion and Management， 2016，129：250-261.
10	REYES J， PARSONS R， HOEMSEN R. Winter happens： the effect of ambient temperature on the travel range of electric vehicles［J］. IEEE Transactions on Vehicular Technology， 2016，65（6）：4016-4022.
11	JEFFERS M， CHANEY L， RUGH J. Climate control load reduction strategies for electric drive vehicles in warm weather［C］. SAE World Congress and Exhibition， 2015：1884-2022.
12	TETE P， GUPTA M， JOSHI S. Developments in battery thermal management systems for electric vehicles： a technical review［J］. Journal of Energy Storage， 2021， 35：102255.
13	罗玉涛，何小颤. 动力锂离子电池热安全性影响因素的研究［J］.汽车工程，2012，34（4）：333-338.
	LUO Y T， HE X C. Research on temperature characteristics simulation and of lithium-ion battery pack for electric vehicle［J］. Automotive Engineering， 2012，34（4）：333-338.
14	LI X， HE F， MA L. Thermal management of cylindrical batteries investigated using wind tunnel testing and computational fluid dynamics simulation［J］. Journal of Power Sources，2013，238： 395-402.
15	CHOI S， KANG M. Prediction of thermal behaviors of an air-cooled lithium-ion battery system for hybrid electric vehicles［J］. Journal of Power Sources， 2014，270： 273-280.
16	WU W， WANG S， WU W， et al. A critical review of battery thermal performance and liquid based battery thermal management［J］. Energy Conversion and Management， 2019，182： 262-281.
17	WANG Q， JIANG B， LI B， et al. A critical review of thermal management models and solutions of lithium-ion batteries for the development of pure electric vehicles［J］. Renewable and Sustainable Energy Reviews， 2016， 64：106-128.
18	JIA E， HAN D， QIU A， et al. Orthogonal experimental design of liquid-cooling structure on the cooling effect of a liquid-cooled battery thermal management system［J］. Applied Thermal Engineering， 2018， 132：508-520.
19	GAO X， MA Y， CHEN H. Active thermal control of a battery pack under elevated temperatures［C］. IFAC Conference on Engine and Powertrain Control， Simulation and Modeling. China： 2018：262-267.
20	MURASHKO K， WU H， PYRHONEN J. Modelling of the battery pack thermal management system for hybrid electric vehicles［C］. 16th European Conference on Power Electronics and Applications. Europe：2014.
21	MASOUDI Y， AZAD N. MPC-based battery thermal management controller for plug-in hybrid electric vehicles［C］. American Control Conference， Washington： 2017：4365-4370.
22	BAUER S， SUCHANECK A， LEON F. Thermal and energy battery management optimization in electric vehicles using Pontryagin's maximum principle［J］. Journal of Power Sources， 2014，246：808-818.
23	TAO X， WAGNER J. Cooling air temperature and mass flow rate control for hybrid electric vehicle battery thermal management［C］. Dynamic Systems and Control Conference， USA： 2014.
24	PHAM T， VAN D， BOSCH P， et al. Cost-effective energy management for hybrid electric heavy-duty truck including battery aging［C］. Dynamic Systems and Control Conference. USA：2013.
25	YUKSEL T， LITSTER S， VISWANATHAN V， et al. Plug-in hybrid electric vehicle LiFePO₄ battery life implications of thermal management， driving conditions， and regional climate［J］. Journal of Power Sources， 2017，338：49-64.
26	LOPEZ J， OCAMPO C， ÁLVAREZ J， et al. Thermal management in plug-in hybrid electric vehicles： a real-time nonlinear model predictive control implementation［J］. IEEE Transactions on Vehicular Technology， 2017，66（9）：7751-7760.
27	ZHU C， LU F， ZHANG H， et al. Robust predictive battery thermal management strategy for connected and automated hybrid electric vehicles based on thermoelectric parameter uncertainty［J］. IEEE Journal of Emerging and Selected Topics in Power Electronics， 2018，6（4）： 1796-1805.
28	WANG H， MENG Y， ZHANG Q， et al. MPC-based precision cooling strategy （PCS） for efficient thermal management of automotive air conditioning system［C］. Control Technology and Applications， China： 2019：573 -578.
29	WANG H， AMINI M， HU Q， et al， Eco-cooling control strategy for automotive air-conditioning system： design and experimental validation［J］. IEEE Transactions on Control Systems Technology，2021，29：2339-2350.
30	MASOUDI Y， MOZAFFARI A， AZAD N. Battery thermal management of electric vehicles： an optimal control approach［C］. Dynamic Systems and Control Conference. USA：2015.
31	LUUS R. Application of dynamic programming to high-dimensional non-linear optimal control problems ［J］. International Journal of Control， 1990，52：239-250.
32	BOJKOV B， LUUS R. Use of random admissible values for control in iterative dynamic programming［J］. Industrial and Engineering Chemistry Research， 1992， 31：1308-1314.
33	LUUS R. Time-optimal control by iterative dynamic programming［J］. Industrial and Engineering Chemistry Research， 1994，33：1486-1492.
34	BOJKOV B， LUUS R. Time optimal control of high dimensional system by iterative dynamic programming ［J］. The Canadian Journal of Chemical Engineering， 1995，73：380-390.
35	BERNARDI D， PAWLIKOWSKI E， NEWMAN J. General energy balance for battery systems［J］. Journal of the Electrochemical Society，1985，132（1）：5-12.
36	XU M， ZHANG Z Q， WANG Xia， et al. Two-dimensional electrochemical-thermal coupled modeling of cylindrical LiFePO₄ batteries［J］. Journal of Power Sources，2014， 256：233-243.
37	XIE Y， ZHENG J T， HU X S， et al. An improved resistance-based thermal model for prismatic lithium-ion battery charging［J］. Applied Thermal Engineering，2020， 180： 115794.
38	XIONG R， HE H W， ZHAO K. Research on an online identification algorithm for a thevenin battery model by an experimental approach ［J］. International Journal of Green Energy， 2015， 12（3）：272-278.
39	MINIGUANO H， BARRADO A， LAZARO A， et al. General parameter identification procedure and comparative study of li-ion battery models［J］. IEEE Transactions on Vehicular Technology， 2020，69（1）： 235 -245.
40	ZHOU Y， WANG B C， LI H X， et al. A surrogate-assisted teaching-learning-based optimization for parameter identification of the battery model［J］. IEEE Transactions on Industrial Informatics， 2020，17（9）：5909-5918.
41	LIANG J， GAN Y， LI Y. Investigation on the thermal performance of a battery thermal management system using heat pipe under different ambient temperatures ［J］. Energy Conversion and Management，2018，155：1-9.
42	SAHEL D， AMEUR H， BENZEGUIR R， et al. Enhancement of heat transfer in a rectangular channel with perforated baffles［J］. Applied Thermal Engineering， 2016，101：156-164.
43	YING X. Model-based virtual thermal sensors for lithium-ion battery in EV applications［J］. IEEE Transactions on Industrial Electronics， 2015，62（5）：3112 -3122.
44	MA Y， MOU H， ZHAO H. Cooling optimization strategy for lithium-ion batteries based on triple-step nonlinear method［J］. Energy， 2020，201：117368.
45	MA Y， CUI Y， MOU H， et al. Core temperature estimation of lithium-ion battery for EV’s using Kalman filter［J］. Applied Thermal Engineering， 2020，168： 114816.
46	茹敬佩. 基于风冷散热的电动汽车电池组热模型与温度控制研究［D］. 长春：吉林大学， 2017.
	RU J P. A study on thermal model and temperature control of an air-cooled battery pack for electric vehicles［D］. Changchun： Jilin University， 2017.
47	WAHL H， GAUTERIN F. An iterative dynamic programming approach for the global optimal control of hybrid electric vehicles under real-time constraints［C］. IEEE Intelligent Vehicles Symposium. Australia： 2013： 592-597.
48	DOAN V， FUJIMOTO H， KOSEKI T， et al. Iterative dynamic programming for optimal control problem with isoperimetric constraint and its application to optimal eco-driving control of electric vehicle［J］. IEEJ Journal of Industry Applications， 2018，7（1）：80-92.
49	MA L， LI J. A novel integrated iterative dynamic programming control strategy for batch processes［C］. 2019 Chinese Automation Congress. China： 2019：2760 -2765.
50	WANG R， LUKIC S. Dynamic programming technique in hybrid electric vehicle optimization［C］. 2012 IEEE International Electric Vehicle Conference. 2012：1-8.
51	LOPEZ J， OCAMPO C， ALVAREZ J， et al. Nonlinear model predictive control for thermal management in plug-in hybrid electric vehicles［J］. IEEE Transactions on Vehicular Technology， 2017，66（5）：3632–3644.
52	ZHU C， LU F， ZHANG H， et al. A real-time battery thermal management strategy for connected and automated hybrid electric vehicles （CAHEVs） based on iterative dynamic programming［J］. IEEE Transactions on Vehicular Technology，2018，67（9）：8077-8084.
53	WANG H， AMINI M， HU Q， et al. Eco-cooling control strategy for automotive air-conditioning system： design and experimental validation［J］. IEEE Transactions on Control Systems Technology，2021，29（6）：2339-2350.

[1]	李贵敬,谷青锴,杨昊鑫,黄健齐,邸立明. PA/EG耦合风冷电池热管理系统轻量研究[J]. 汽车工程, 2023, 45(2): 209-218.
[2]	路兴隆,张甫仁,赵海波,孙世政,李雪,赵浩东. 基于同心圆结构的新型液冷板优化设计及其性能研究[J]. 汽车工程, 2023, 45(11): 2058-2069.
[3]	冯能莲, 董士康, 李德壮, 陈龙科, 丰收. 蜂巢式液冷电池模块传热特性的试验研究^*[J]. 汽车工程, 2020, 42(5): 658-664.
[4]	彭运赛, 夏飞, 袁博, 王志成, 罗志疆. 基于改进CNN和信息融合的动力电池组故障诊断方法^*[J]. 汽车工程, 2020, 42(11): 1529-1536.