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Design optimization of battery pack enclosure for electric vehicle

  • Li Shui
  • Fangyuan Chen
  • Akhil Garg
  • Xiongbin Peng
  • Nengsheng Bao
  • Jian Zhang
INDUSTRIAL APPLICATION

Abstract

Lithium-ion Battery pack which is comprised of assembly of battery modules is the main source of power transmission for electric vehicles. During the actual operation of electric vehicle, the battery packs and its enclosure is subjected to harsh environmental conditions such as the external vibrations and shocks due to varying road slopes. This will result in stresses and deformations of different degrees. The vehicle safety heavily depends on on the safety of battery pack which in turn is dependent on its mechanical features, such as the ability to resist deformation and vibration shocks. In addition, lighter weight vehicle is preferred because it can increase the range of vehicle and the life cycle of a battery pack. In this study, a design optimization methodology is proposed to optimize the features of mechanical design (e.g. minimization of mass, maximization of minimum natural frequency and minimization of maximum deformation) of the battery pack enclosure. The proposed methodology is comprised of four phases. In the first phase, finite element models for maximum deformation (based on static analysis), minimum natural frequency (based on modal analysis) and the mass are developed by using the combination of four methods (i.e. central composite design (CCD) and response surface methodology (RSM), CCD and artificial neural network (ANN), Latin hypercube sampling (LHS) and RSM, LHS and ANN). In the second phase, the best combination of methodology (CCD and ANN) is then selected for experimental design and the empirical models are formulated for three features of mechanical design. In the third phase, the models based on CCD and ANN for the maximum deformation, minimum natural frequency and mass are further optimized by using non-dominated sorted genetic algorithm (NSGA II). In the fourth phase, the optimum combination of inputs obtained by using NSGA II is used for the manufacturing of battery pack enclosure. Conclusions are made and research recommendations are proposed for the future work.

Keywords

Battery packs Mechanical design Electric vehicle Design optimization CCD and ANN 

Notes

Acknowledgements

Supports provided by engineers in Shantou Institute for Light Industry Equipment Research for the development of the case study are gratefully acknowledged. The authors also wish to thank the National Natural Science Foundation of China [grant number 51375287, 51505269], Shantou University Scientific Research Funded Project [Grant No. NTF 16002, NTF 16011], as well as the sailing talent project and Shantou University National fund cultivation project for providing financial supports to this research.

References

  1. Abada S, Marlair G, Lecocq A, Petit M, Sauvant-Moynot V, Huet F (2016) Safety focused modelling of lithium-ion batteries: a review. J Power Sources 306:178–192CrossRefGoogle Scholar
  2. Aneke M, Wang M (2016) Energy storage technologies and real life applications–a state of the art review. Appl Energy 179:350–377CrossRefGoogle Scholar
  3. Arora S, Shen W, Kapoor A (2016) Review of mechanical design and strategic placement technique of a robust battery pack for electric vehicles. Renew Sust Energ Rev 60:1319–1331CrossRefGoogle Scholar
  4. Berecibar M, Gandiaga I, Villarreal I, Omar N, Van Mierlo J, Van den Bossche P (2016) Critical review of state of health estimation methods of Li-ion batteries for real applications. Renew Sust Energ Rev 56:572–587CrossRefGoogle Scholar
  5. Brand MJ, Schuster SF, Bach T, Fleder E, Stelz M et al (2015) Effects of vibrations and shocks on lithium-ion cells. J Power Sources 288:62–69CrossRefGoogle Scholar
  6. Cannarella J, Arnold CB (2014) State of health and charge measurements in lithium-ion batteries using mechanical stress. J Power Sources 269:7–14CrossRefGoogle Scholar
  7. Chen Y, Liu G, Zhang Z, Hou S (2017) Integrated design technique for materials and structures of vehicle body under crash safety considerations. Struct Multidiscip Optim 1–18Google Scholar
  8. Choi CH, Cho JM, Kil Y, Yoon Y (2013) Development of polymer composite battery pack case for an electric vehicle. SAE Technical PaperGoogle Scholar
  9. Cuma MU, Koroglu T (2015) A comprehensive review on estimation strategies used in hybrid and battery electric vehicles. Renew Sust Energ Rev 42:517–531CrossRefGoogle Scholar
  10. Das GK, Hazra B, Garg A, Ng CWW (2018) Stochastic hydro-mechanical stability of vegetated slopes: an integrated copula based framework. Catena 160:124–133CrossRefGoogle Scholar
  11. Du J, Ouyang D (2017) Progress of Chinese electric vehicles industrialization in 2015: a review. Appl Energy 188:529–546CrossRefGoogle Scholar
  12. Dubarry M, Berecibar M, Devie A, Anseán D, Omar N, Villarreal I (2017) State of health battery estimator enabling degradation diagnosis: model and algorithm description. J Power Sources 360:59–69CrossRefGoogle Scholar
  13. Garg A, Chen F, Zhang J (2016) State-of-the-art of designs studies for batteries packs of electric vehicles. IET Conf Electr Veh 29–6Google Scholar
  14. Garg A, Vijayaraghavan V, Zhang J, Li S, Liang X (2017a) Design of robust battery capacity model for electric vehicle by incorporation of uncertainties. Int J Energy Res. 41(10):1436–1451.  https://doi.org/10.1002/er.3723
  15. Garg A, Vijayaraghavan V, Zhang J, Lam JSL (2017b) Robust model design for evaluation of power characteristics of the cleaner energy system. Renew Energy 112:302–313CrossRefGoogle Scholar
  16. Garg A, Li J, Hou J, Berretta C, Garg A (2017c) A new computational approach for estimation of wilting point for green infrastructure. Measurement 111:351–358CrossRefGoogle Scholar
  17. Hang Y, Qu M, Ukkusuri S (2011) Optimizing the design of a solar cooling system using central composite design techniques. Energ Buildings 43(4):988–994CrossRefGoogle Scholar
  18. He LY, Chen Y (2013) Thou shalt drive electric and hybrid vehicles: scenario analysis on energy saving and emission mitigation for road transportation sector in China. Transp Policy 25:30–40CrossRefGoogle Scholar
  19. Hooper JM, Marco J (2013) Understanding vibration frequencies experienced by electric vehicle batteries. IET Hybrid Electr Veh Conf 2013 (HEVC 2013) 9.1Google Scholar
  20. Hooper J, Marco J (2015) Experimental modal analysis of lithium-ion pouch cells. J Power Sources 285:247–259CrossRefGoogle Scholar
  21. Huang Y, Gao L, Yi Z, Tai K, Kalita P, Prapainainar P, Garg A (2018) An application of evolutionary system identification algorithm in modelling of energy production system. Measurement 114:122–131CrossRefGoogle Scholar
  22. Huo H, Wang M, Zhang X, He K, Gong H, Jiang K et al (2012) Projection of energy use and greenhouse gas emissions by motor vehicles in China: policy options and impacts. Energy Policy 43:37–48CrossRefGoogle Scholar
  23. Jaguemont J, Boulon L, Dubé Y (2016) A comprehensive review of lithium-ion batteries used in hybrid and electric vehicles at cold temperatures. Appl Energy 164:99–114CrossRefGoogle Scholar
  24. Javani N, Dincer I, Naterer GF, Rohrauer GL (2014) Modelling of passive thermal management for electric vehicle battery packs with PCM between cells. Appl Therm Eng 73(1):307–316CrossRefGoogle Scholar
  25. Jin X, Huang K (2016) Multiphysics modeling of solid-oxide iron–air redox battery: analysis and optimization of operation and performance parameters. Sci Bull 61(17):1345–1354CrossRefGoogle Scholar
  26. Lang JF, Kjell G (2015) Comparing vibration measurements in an electric vehicle with standard vibration requirements for Li-ion batteries using power spectral density analysis. Int J Electr Hybrid Veh 7(3):272–286CrossRefGoogle Scholar
  27. Liu B, Yin S, Xu J (2016) Integrated computation model of lithium-ion battery subject to nail penetration. Appl Energy 183:278–289CrossRefGoogle Scholar
  28. Lu L, Han X, Li J, Hua J, Ouyang M (2013) A review on the key issues for lithium-ion battery management in electric vehicles. J Power Sources 226:272–288CrossRefGoogle Scholar
  29. Lu W, Xiao-kai C, Qing-hai Z (2016) Muti-objective topology optimization of an electric vehicle’s traction battery enclosure. Energy Procedia 88:874–880CrossRefGoogle Scholar
  30. Mazidi M, Zakariazadeh A, Jadid S, Siano P (2014) Integrated scheduling of renewable generation and demand response programs in a microgrid. Energy Convers Manag 86:1118–1127CrossRefGoogle Scholar
  31. Qin R, Shao G, Hou J, Zheng Z, Zhai T, Li H (2017) One-pot synthesis of Li3VO4@ C nanofibers by electrospinning with enhanced electrochemical performance for lithium-ion batteries. Sci Bull.  https://doi.org/10.1016/j.scib.2017.07.001
  32. Ramadesigan V (2017) Electrochemical-engineering-based models for lithium-ion batteries—past, present, and future. Electrochem Soc Interface 26(2):69–71CrossRefGoogle Scholar
  33. Reddy PR, Reddy PS, Reddy KVK (2014) Vibration analysis of a torpedo battery tray using FEA. Int J Res Eng Technol (IJRET) eISSN:2319–1163Google Scholar
  34. Sun F, Xiong R, He H (2016) A systematic state-of-charge estimation framework for multi-cell battery pack in electric vehicles using bias correction technique. Appl Energy 162:1399–1409CrossRefGoogle Scholar
  35. Tie SF, Tan CW (2013) A review of energy sources and energy management system in electric vehicles. Renew Sust Energ Rev 20:82–102CrossRefGoogle Scholar
  36. Wang W, Fleischer C, Sauer DU (2014) Critical review of the methods for monitoring of lithium-ion batteries in electric and hybrid vehicles. J Power Sources 258:321–339CrossRefGoogle Scholar
  37. Wang QK, He YJ, Shen JN, Ma ZF, Zhong GB (2017) A unified modelling framework for lithium-ion batteries: an artificial neural network based thermal coupled equivalent circuit model approach. Energy 138:118–132CrossRefGoogle Scholar
  38. Yang DC, Jang IS, Jang MH, Park CN, Park CJ, Choi J (2009) Optimization of additive compositions for anode in Ni-MH secondary battery using the response surface method. Met Mater Int 15(3):421–425CrossRefGoogle Scholar
  39. Yi TF, Li YM, Li XY, Pan JJ, Zhang Q, Zhu YR (2017) Enhanced electrochemical property of FePO4-coated LiNi0. 5Mn1. 5O4 as cathode materials for Li-ion battery. Sci Bull 62(14):1004–1010CrossRefGoogle Scholar
  40. Zhang Q, Huo Y, Rao Z (2016) Numerical study on solid–liquid phase change in paraffin as phase change material for battery thermal management. Sci bull 61(5):391–400CrossRefGoogle Scholar
  41. Zhao B, Zhang X, Chen J, Wang C, Guo L (2013) Operation optimization of standalone microgrids considering lifetime characteristics of battery energy storage system. IEEE Trans Sust Energ 4(4):934–943CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Mechatronics EngineeringShantou UniversityShantouChina
  2. 2.Intelligent Manufacturing Key Laboratory of Ministry of EducationShantou UniversityShantouChina
  3. 3.Shantou Institute for Light Industrial Equipment ResearchShantouChina

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