动力锂离子电池仿真模型研究进展
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摘要
锂离子电池作为新能源电动汽车优异的动力来源受到广泛关注,获得高性能的锂离子电池对电动汽车的发展至关重要。数值仿真技术突破了传统实验的限制而极大地促进了锂离子电池的研究工作。高效、实用的仿真模型可以将多种化学反应及物理场相互耦合,预测多种因素对于电池各种性能的影响,使仿真结果尽可能地接近真实情况。本文主要介绍了仿真研究的优势和重要意义,分别从电池热模型、电学特性模型、老化模型等出发,比较了众多仿真模型针对锂离子电池性能的仿真结果,总结不同模型的优势以及存在的薄弱环节,并提出仿真研究以后的发展趋势为:①从机理出发,研究多物理场相互作用关系,实现多场耦合;②从模型和算法入手,扩大模型的研究范围,兼顾简化模型和提高精确度;③从电池本身入手,注重电池材料的性能改善以及成组方式和结构优化。
Lithium-ion batteries have received extensive attention as an excellent power source for new energy electric vehicles, and high-performance lithium-ion batteries are very important to the development of electric vehicles. Numerical simulation technology has overcome the limitations of traditional experiments and greatly promotes the research of lithium-ion batteries. Simulation models can couple multiple chemical reactions and physical fields, making it efficiently to predict the impact of various factors on the battery performance. And the biggest challenge for designing the battery models is to make the simulation results as close as possible to the real situation. Battery thermal model,perspectives of electrical model, the aging model and other models are applied in this paper to compare the simulation results about lithium-ion batteries. Besides, the advantages and disadvantages of each model are outlined. Furthermore, this paper puts forward the future developing trends of simulation: ① to explore the interaction relationship of multiple physical fields; ② to extend the applications of the models;③ to improve the performance of battery materials and optimize the assembly method and the structure.
Lithium-ion batteries have received extensive attention as an excellent power source for new energy electric vehicles, and high-performance lithium-ion batteries are very important to the development of electric vehicles. Numerical simulation technology has overcome the limitations of traditional experiments and greatly promotes the research of lithium-ion batteries. Simulation models can couple multiple chemical reactions and physical fields, making it efficiently to predict the impact of various factors on the battery performance. And the biggest challenge for designing the battery models is to make the simulation results as close as possible to the real situation. Battery thermal model,perspectives of electrical model, the aging model and other models are applied in this paper to compare the simulation results about lithium-ion batteries. Besides, the advantages and disadvantages of each model are outlined. Furthermore, this paper puts forward the future developing trends of simulation: ① to explore the interaction relationship of multiple physical fields; ② to extend the applications of the models;③ to improve the performance of battery materials and optimize the assembly method and the structure.
引文
[1]程昀,李劼,贾明,等.锂离子电池多尺度数值模型的应用现状及发展前景[J].物理学报, 2015, 64(21):137-152.CHENG Y, LI J, JIA M, et al. Application status and future of multiscale numerical models for lithium ion battery[J]. Acta Phys. Sin.,2015, 64(21):137-152.
[2] LIU H Q, WEI Z B, HE WD, et al. Thermal issues about Li-ion batteries and recent progress in battery thermal management systems:a review[J]. Energy Conversion&Management, 2017, 150:304-330.
[3] BERNARDI D, PAWLIKOWSKI E, NEWMAN J. A general energybalance for battery systems[J]. Journal of the Electrochemical Society,1985, 132(1):5-12.
[4] LAI Y Q, DU S L, AI L, et al. Insight into heat generation of lithium ion batteries based on the electrochemical-thermal model at high discharge rates[J]. International Journal of Hydrogen Energy, 2015, 40(38):13039-13049.
[5] SONG L B, LI L, XIAO Z L, et al. Estimation of temperature distribution of LiFePO4lithium ion battery during charge-discharge process[J]. Ionics, 2016, 22(9):1517-1525.
[6] XIAO Z L, ZHOU Q Q, SONG L B, et al. Assessment of thermoelectrochemical performance on cathode materials for lithium ion cells[J]. Int. J. Electrochem. Sci., 2016, 11:2825-2834.
[7] SONG L B, XIAO Z L, LI L J, et al. Thermo-electrochemical study on cathode materials for lithium ion cells[J]. Journal of Solid State Electrochemistry, 2015, 19(7):2167-2175.
[8] SONG L B, LIU J, XIAO Z L, et al. Thermo-eletrochemical study on LiNi0.8Co0.1Mn0.1O2with in situ modification of Li2ZrO3[J]. Ionics, 2018(1):1-11.
[9] GHALKHANI M, BAHIRAEI F, NAZRI G A, et al. Electrochemicalthermal model of pouch-type lithium-ion batteries[J]. Electrochimica Acta, 2017, 247:569-587.
[10]殷宝华,艾亮,杨治安,等.锂离子电池模块热模拟仿真[J].电源技术, 2017, 41(5):696-698.YIN B H, AI L, YANG Z A, et al. Thermal simulation of lithium ion battery module[J]. Chinese Journal of Power Sources, 2017, 41(5):696-698.
[11] FENG X N, OUYANG M G, LIU X, et al. Thermal runaway mechanism of lithium ion battery for electric vehicles:a review[J]. Energy Storage Materials, 2017, 10:246-267.
[12] DONG T, PENG P, JIANG F M. Numerical modeling and analysis of the thermal behavior of NCM lithium-ion batteries subjected to very high C-rate discharge/charge operations[J]. International Journal of Heat&Mass Transfer, 2018, 117:261-272.
[13] ZHANG C, SANTHANAGOPALAN S, SPRAGUE M A, et al. Coupled mechanical-electrical-thermal modeling for short-circuit prediction in a lithium-ion cell under mechanical abuse[J]. Journal of Power Sources, 2015, 290:102-113.
[14] SHAHID S, AGELIN-CHAAB M. Experimental and numerical studies on air cooling and temperature uniformity in a battery pack[J].International Journal of Energy Research, 2018(1):1-17.
[15] BAI F, CHEN M, SONG W, et al. Thermal management performances of PCM/Water cooling-plate using for lithium-ion battery module based on non-uniform internal heat source[J]. Applied Thermal Engineering, 2017, 126:17-27.
[16]靳鹏超,王世学.一种使用相变材料的新型电动汽车电池热管理系统[J].化工进展, 2014, 33(10):2608-2612.JIN P C, WANG S X. A novel thermal management system for EV batteries using phase-change material[J]. Chemical Industry and Engineering Progess, 2014, 33(10):2608-2612.
[17]曾健,陆龙生,陈维,等.基于热管技术的锂离子动力电池散热系统[J].化工进展, 2015, 34(1):37-43.ZENG J, LU L S, CHEN W, et al. Thermal control module using heat pipe for lithium-ion battery[J]. Chemical Industry and Engineering Progess, 2015, 34(1):37-43.
[18] XIA G D, CAO L, BI G L, et al. A review on battery thermal management in electric vehicle application[J]. Journal of Power Sources, 2017, 367:90-105.
[19]程昀,李劼,贾明,等.动力锂离子电池模块散热结构仿真研究[J].中国有色金属学报, 2015, 25(6):1607-1616.CHENG Y, LI J, JIA M, et al. Simulation research of heat dissipation structure for automotive lithium-ion battery packs[J]. The Chinese Journal of Nonferrous Metals, 2015, 25(6):1607-1616.
[20] MOHAMMADIAN S K, ZHANG Y W. Improving wettability and preventing Li-ion batteries from thermal runaway using microchannels[J]. International Journal of Heat&Mass Transfer, 2017, 118:911-918.
[21] DANG X J, LI Y, XU K, et al. Open-circuit voltage-based state of charge estimation of lithium-ion battery using dual neural network fusion battery model[J]. Electrochimica Acta, 2016, 188(10):356-366.
[22] NUHIC A, TERZIMEHIC T, SOCZKA-GUTH T, et al. Health diagnosis and remaining useful life prognostics of lithium-ion batteries using data-driven methods[J]. Journal of Power Sources, 2013, 239(1):680-688.
[23] FLEISCHER C, WAAG W, BAI Z, et al. On-line self-learning time forward voltage prognosis for lithium-ion batteries using adaptive neuro-fuzzy inference system[J]. Journal of Power Sources, 2013, 243(6):728-749.
[24] HU X S, LI S B, PENG H E. A comparative study of equivalent circuit models for Li-ion batteries[J]. Journal of Power Sources, 2012, 198:359-367.
[25] LEE S J, KIM J H, LEE J M, et al. The state and parameter estimation of an Li-ion battery using a new OCV-SOC concept[C]//Power Electronics Specialists Conference, 2007. Pesc. IEEE, 2007:2799-2803.
[26] GAO M Y, LIU Y Y, HE Z W. Battery state of charge online estimation based on particle filter[C]//International Congress on Image and Signal Processing. IEEE, 2011:2233-2236.
[27] KIM I S. Nonlinear state of charge estimator for hybrid electric vehicle battery[J]. IEEE Transactions on Power Electronics, 2008, 23(4):2027-2034.
[28] CHARKHGARD M, ZARIF M H. Design of adaptive H∞, filter for implementing on state-of-charge estimation based on battery state-ofcharge-varying modelling[J]. Power Electronics Iet, 2015, 8(10):1825-1833.
[29] WANG Q Q, KANG J Q, TAN Z X, et al. An online method to simultaneously identify the parameters and estimate states for lithium ion batteries[J]. Electrochimica Acta, 2018, 289:376-388.
[30] DIN M S E, HUSSEIN A A, ABDEL-HAFEZ M F. Improved battery SOC estimation accuracy using a modified UKF with an adaptive cell model under real EV operating conditions[J]. IEEE Transactions on Transportation Electrification, 2018, 4(2):408-417.
[31] DOYLE M, FULLER T F, NEWMAN J S. Modeling of galvanostatic charge and discharge of the lithium/polymer/insertion cell[J]. Journal of the Electrochemical Society, 1993, 140(6):1526-1533.
[32] NEWMAN J S, THOMAS K E, HAFEZI H, et al. Modeling of lithiumion batteries[J]. Journal of Power Sources, 2003, s119/120/121(3):838-843.
[33] SANTHANAGOPALAN S, GUO Q, RAMADASS P, et al. Review of models for predicting the cycling performance of lithium ion batteries[J]. Journal of Power Sources, 2006, 156(2):620-628.
[34] ZOU C, MANZIE C, NE?I?D. A framework for simplification of PDEbased lithium-ion battery models[J]. IEEE Transactions on Control Systems Technology, 2016, 24(5):1594-1609.
[35]王靖,柯少勇,黄贤坤,等.锂离子电池电极颗粒分布对电化学性能影响的分析[J].化工进展, 2018, 37(7):2620-2626.WANG J, KE S Y, HUANG X K, et al. Analysis of the effects of electrode particle size distribution on the electrochemical performances of lithium ion battery[J]. Chemical Industry and Engineering Progess, 2018, 37(7):2620-2626.
[36] BARRéA, DEGUILHEM B, GROLLEAU S, et al. A review on lithium-ion battery ageing mechanisms and estimations for automotive applications[J]. Journal of Power Sources, 2013, 241(11):680-689.
[37] LI Z, HUANG J, LIAW B Y, et al. A review of lithium deposition in lithium-ion and lithium metal secondary batteries[J]. Journal of Power Sources, 2014, 254:168-182.
[38] RAMADASS P, HARAN B, GOMADAM P M, et al. Development of first principles capacity fade model for Li-ion cells[J]. Journal of the Electrochemical Society, 2004, 151(2):A196-A203.
[39] SAFARI M, MORCRETTE M, TEYSSOT A, et al. Multimodal physicsbased aging model for life prediction of Li-ion batteries[J]. Physical Review A, 2009, 156(3):100-100.
[40] BAEK K W, HONG E S, CHA S W. Capacity fade modeling of a lithium-ion battery for electric vehicles[J]. International Journal of Automotive Technology, 2015, 16(2):309-315.
[41]蒋跃辉,艾亮,贾明,等.基于动态参数响应模型的动力锂离子电池循环容量衰减研究[J].物理学报, 2017, 66(11):328-338.JIANG Y H, AI L, JIA M, et al. Cyclic capacity fading of the power lithium ion battery based on a numerical modelling with dynamic responses[J]. Acta Phys. Sin., 2017, 66(11):328-338.
[42] SCHUSTER S F, BACH T, FLEDER E, et al. Nonlinear aging characteristics of lithium-ion cells under different operational conditions[J]. Journal of Energy Storage, 2015, 1(1):44-53.
[43] ARORA P, DOYLE M, WHITE R E. Mathematical modeling of the lithium deposition overcharge reaction in lithium-ion batteries using carbon-based negative electrodes[J]. Promotion&Education, 1999,146(10):3543-3553.
[44] TANG M, ALBERTUS P, NEWMAN J. Two-dimensional modeling of lithium deposition during cell charging[J]. Journal of the Electrochemical Society, 2009, 51(2):131-157.
[45] YANG X G, LENG Y, ZHANG G, et al. Modeling of lithium plating induced aging of lithium-ion batteries:transition from linear to nonlinear aging[J]. Journal of Power Sources, 2017, 360:28-40.
[46]李宗赞.应力及材料塑性变形对锂离子电池性能的影响[D].上海:上海大学, 2015.LI Z Z. Impacts of stress and plastic deformation on the performance of lithium ion batteries[D]. Shanghai:Shanghai University, 2015.
[47] SONG Y C, SOH A K, ZHANG J Q. On stress-induced voltage hysteresis in lithium ion batteries:impacts of material property, charge rate and particle size[J]. Journal of Materials Science, 2016, 51(21):1-10.
[48]李书国,艾亮,贾明,等.基于电化学热耦合模型的锂离子动力电池极化特性[J].中国有色金属学报, 2018(1):142-149.LI S G, AI L, JIA M, et al. Polarization characteristics of lithium ion power battery based on electrochemical-thermal model[J]. The Chinese Journal of Nonferrous Metals, 2018(1):142-149.
[2] LIU H Q, WEI Z B, HE WD, et al. Thermal issues about Li-ion batteries and recent progress in battery thermal management systems:a review[J]. Energy Conversion&Management, 2017, 150:304-330.
[3] BERNARDI D, PAWLIKOWSKI E, NEWMAN J. A general energybalance for battery systems[J]. Journal of the Electrochemical Society,1985, 132(1):5-12.
[4] LAI Y Q, DU S L, AI L, et al. Insight into heat generation of lithium ion batteries based on the electrochemical-thermal model at high discharge rates[J]. International Journal of Hydrogen Energy, 2015, 40(38):13039-13049.
[5] SONG L B, LI L, XIAO Z L, et al. Estimation of temperature distribution of LiFePO4lithium ion battery during charge-discharge process[J]. Ionics, 2016, 22(9):1517-1525.
[6] XIAO Z L, ZHOU Q Q, SONG L B, et al. Assessment of thermoelectrochemical performance on cathode materials for lithium ion cells[J]. Int. J. Electrochem. Sci., 2016, 11:2825-2834.
[7] SONG L B, XIAO Z L, LI L J, et al. Thermo-electrochemical study on cathode materials for lithium ion cells[J]. Journal of Solid State Electrochemistry, 2015, 19(7):2167-2175.
[8] SONG L B, LIU J, XIAO Z L, et al. Thermo-eletrochemical study on LiNi0.8Co0.1Mn0.1O2with in situ modification of Li2ZrO3[J]. Ionics, 2018(1):1-11.
[9] GHALKHANI M, BAHIRAEI F, NAZRI G A, et al. Electrochemicalthermal model of pouch-type lithium-ion batteries[J]. Electrochimica Acta, 2017, 247:569-587.
[10]殷宝华,艾亮,杨治安,等.锂离子电池模块热模拟仿真[J].电源技术, 2017, 41(5):696-698.YIN B H, AI L, YANG Z A, et al. Thermal simulation of lithium ion battery module[J]. Chinese Journal of Power Sources, 2017, 41(5):696-698.
[11] FENG X N, OUYANG M G, LIU X, et al. Thermal runaway mechanism of lithium ion battery for electric vehicles:a review[J]. Energy Storage Materials, 2017, 10:246-267.
[12] DONG T, PENG P, JIANG F M. Numerical modeling and analysis of the thermal behavior of NCM lithium-ion batteries subjected to very high C-rate discharge/charge operations[J]. International Journal of Heat&Mass Transfer, 2018, 117:261-272.
[13] ZHANG C, SANTHANAGOPALAN S, SPRAGUE M A, et al. Coupled mechanical-electrical-thermal modeling for short-circuit prediction in a lithium-ion cell under mechanical abuse[J]. Journal of Power Sources, 2015, 290:102-113.
[14] SHAHID S, AGELIN-CHAAB M. Experimental and numerical studies on air cooling and temperature uniformity in a battery pack[J].International Journal of Energy Research, 2018(1):1-17.
[15] BAI F, CHEN M, SONG W, et al. Thermal management performances of PCM/Water cooling-plate using for lithium-ion battery module based on non-uniform internal heat source[J]. Applied Thermal Engineering, 2017, 126:17-27.
[16]靳鹏超,王世学.一种使用相变材料的新型电动汽车电池热管理系统[J].化工进展, 2014, 33(10):2608-2612.JIN P C, WANG S X. A novel thermal management system for EV batteries using phase-change material[J]. Chemical Industry and Engineering Progess, 2014, 33(10):2608-2612.
[17]曾健,陆龙生,陈维,等.基于热管技术的锂离子动力电池散热系统[J].化工进展, 2015, 34(1):37-43.ZENG J, LU L S, CHEN W, et al. Thermal control module using heat pipe for lithium-ion battery[J]. Chemical Industry and Engineering Progess, 2015, 34(1):37-43.
[18] XIA G D, CAO L, BI G L, et al. A review on battery thermal management in electric vehicle application[J]. Journal of Power Sources, 2017, 367:90-105.
[19]程昀,李劼,贾明,等.动力锂离子电池模块散热结构仿真研究[J].中国有色金属学报, 2015, 25(6):1607-1616.CHENG Y, LI J, JIA M, et al. Simulation research of heat dissipation structure for automotive lithium-ion battery packs[J]. The Chinese Journal of Nonferrous Metals, 2015, 25(6):1607-1616.
[20] MOHAMMADIAN S K, ZHANG Y W. Improving wettability and preventing Li-ion batteries from thermal runaway using microchannels[J]. International Journal of Heat&Mass Transfer, 2017, 118:911-918.
[21] DANG X J, LI Y, XU K, et al. Open-circuit voltage-based state of charge estimation of lithium-ion battery using dual neural network fusion battery model[J]. Electrochimica Acta, 2016, 188(10):356-366.
[22] NUHIC A, TERZIMEHIC T, SOCZKA-GUTH T, et al. Health diagnosis and remaining useful life prognostics of lithium-ion batteries using data-driven methods[J]. Journal of Power Sources, 2013, 239(1):680-688.
[23] FLEISCHER C, WAAG W, BAI Z, et al. On-line self-learning time forward voltage prognosis for lithium-ion batteries using adaptive neuro-fuzzy inference system[J]. Journal of Power Sources, 2013, 243(6):728-749.
[24] HU X S, LI S B, PENG H E. A comparative study of equivalent circuit models for Li-ion batteries[J]. Journal of Power Sources, 2012, 198:359-367.
[25] LEE S J, KIM J H, LEE J M, et al. The state and parameter estimation of an Li-ion battery using a new OCV-SOC concept[C]//Power Electronics Specialists Conference, 2007. Pesc. IEEE, 2007:2799-2803.
[26] GAO M Y, LIU Y Y, HE Z W. Battery state of charge online estimation based on particle filter[C]//International Congress on Image and Signal Processing. IEEE, 2011:2233-2236.
[27] KIM I S. Nonlinear state of charge estimator for hybrid electric vehicle battery[J]. IEEE Transactions on Power Electronics, 2008, 23(4):2027-2034.
[28] CHARKHGARD M, ZARIF M H. Design of adaptive H∞, filter for implementing on state-of-charge estimation based on battery state-ofcharge-varying modelling[J]. Power Electronics Iet, 2015, 8(10):1825-1833.
[29] WANG Q Q, KANG J Q, TAN Z X, et al. An online method to simultaneously identify the parameters and estimate states for lithium ion batteries[J]. Electrochimica Acta, 2018, 289:376-388.
[30] DIN M S E, HUSSEIN A A, ABDEL-HAFEZ M F. Improved battery SOC estimation accuracy using a modified UKF with an adaptive cell model under real EV operating conditions[J]. IEEE Transactions on Transportation Electrification, 2018, 4(2):408-417.
[31] DOYLE M, FULLER T F, NEWMAN J S. Modeling of galvanostatic charge and discharge of the lithium/polymer/insertion cell[J]. Journal of the Electrochemical Society, 1993, 140(6):1526-1533.
[32] NEWMAN J S, THOMAS K E, HAFEZI H, et al. Modeling of lithiumion batteries[J]. Journal of Power Sources, 2003, s119/120/121(3):838-843.
[33] SANTHANAGOPALAN S, GUO Q, RAMADASS P, et al. Review of models for predicting the cycling performance of lithium ion batteries[J]. Journal of Power Sources, 2006, 156(2):620-628.
[34] ZOU C, MANZIE C, NE?I?D. A framework for simplification of PDEbased lithium-ion battery models[J]. IEEE Transactions on Control Systems Technology, 2016, 24(5):1594-1609.
[35]王靖,柯少勇,黄贤坤,等.锂离子电池电极颗粒分布对电化学性能影响的分析[J].化工进展, 2018, 37(7):2620-2626.WANG J, KE S Y, HUANG X K, et al. Analysis of the effects of electrode particle size distribution on the electrochemical performances of lithium ion battery[J]. Chemical Industry and Engineering Progess, 2018, 37(7):2620-2626.
[36] BARRéA, DEGUILHEM B, GROLLEAU S, et al. A review on lithium-ion battery ageing mechanisms and estimations for automotive applications[J]. Journal of Power Sources, 2013, 241(11):680-689.
[37] LI Z, HUANG J, LIAW B Y, et al. A review of lithium deposition in lithium-ion and lithium metal secondary batteries[J]. Journal of Power Sources, 2014, 254:168-182.
[38] RAMADASS P, HARAN B, GOMADAM P M, et al. Development of first principles capacity fade model for Li-ion cells[J]. Journal of the Electrochemical Society, 2004, 151(2):A196-A203.
[39] SAFARI M, MORCRETTE M, TEYSSOT A, et al. Multimodal physicsbased aging model for life prediction of Li-ion batteries[J]. Physical Review A, 2009, 156(3):100-100.
[40] BAEK K W, HONG E S, CHA S W. Capacity fade modeling of a lithium-ion battery for electric vehicles[J]. International Journal of Automotive Technology, 2015, 16(2):309-315.
[41]蒋跃辉,艾亮,贾明,等.基于动态参数响应模型的动力锂离子电池循环容量衰减研究[J].物理学报, 2017, 66(11):328-338.JIANG Y H, AI L, JIA M, et al. Cyclic capacity fading of the power lithium ion battery based on a numerical modelling with dynamic responses[J]. Acta Phys. Sin., 2017, 66(11):328-338.
[42] SCHUSTER S F, BACH T, FLEDER E, et al. Nonlinear aging characteristics of lithium-ion cells under different operational conditions[J]. Journal of Energy Storage, 2015, 1(1):44-53.
[43] ARORA P, DOYLE M, WHITE R E. Mathematical modeling of the lithium deposition overcharge reaction in lithium-ion batteries using carbon-based negative electrodes[J]. Promotion&Education, 1999,146(10):3543-3553.
[44] TANG M, ALBERTUS P, NEWMAN J. Two-dimensional modeling of lithium deposition during cell charging[J]. Journal of the Electrochemical Society, 2009, 51(2):131-157.
[45] YANG X G, LENG Y, ZHANG G, et al. Modeling of lithium plating induced aging of lithium-ion batteries:transition from linear to nonlinear aging[J]. Journal of Power Sources, 2017, 360:28-40.
[46]李宗赞.应力及材料塑性变形对锂离子电池性能的影响[D].上海:上海大学, 2015.LI Z Z. Impacts of stress and plastic deformation on the performance of lithium ion batteries[D]. Shanghai:Shanghai University, 2015.
[47] SONG Y C, SOH A K, ZHANG J Q. On stress-induced voltage hysteresis in lithium ion batteries:impacts of material property, charge rate and particle size[J]. Journal of Materials Science, 2016, 51(21):1-10.
[48]李书国,艾亮,贾明,等.基于电化学热耦合模型的锂离子动力电池极化特性[J].中国有色金属学报, 2018(1):142-149.LI S G, AI L, JIA M, et al. Polarization characteristics of lithium ion power battery based on electrochemical-thermal model[J]. The Chinese Journal of Nonferrous Metals, 2018(1):142-149.