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A Comparison of Model Order Reduction Techniques for Real-Time Battery Thermal Modelling
Technical Paper
2019-01-0503
ISSN: 0148-7191, e-ISSN: 2688-3627
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English
Abstract
Battery temperature is known to have a critical influence on overall battery pack performance, from electrochemical behavior, charge acceptance, power availability, trip efficiency, safety, reliability and life-cycle costs. Temperature monitoring is critical to ensure safe and reliable battery pack operation.
Monitoring of cell temperatures in battery packs allows for control and estimation algorithms that can ensure homogenous pack temperature distribution, prevent excessive pack temperature rise and even infer cell core temperature, potentially allowing to both predict and mitigate onset of thermal runaway.
The increasing need for improved accuracy requires inclusion of more detail in the modelling stage, leading inevitably to ever larger-scale, ever more complex dynamical systems. Simulations in such large-scale settings lead in turn to unmanageably large demands on computational resources, which is the main motivation for Model Order Reduction.
Model Order Reduction is focused on reducing the complexity of large-scale dynamical systems, while preserving their input-output behavior. Reduced models mimic the complex behavior of large-scale dynamical systems, and can be efficiently used for design, optimization and sensitivity analysis. The resulting reduced order model can be used to replace the original system as a component in a larger simulation or it might be used to develop a simpler and faster controller suitable for real time applications.
Three model order reduction techniques are compared. The first method, Balanced Truncation, assumes access to the high-fidelity model structure is available whilst the other two, Nyquist and neural network approximation, assume only input/output behavioral knowledge is available. The reduced order models are compared, in simulation, to a high-fidelity model of a battery pack in terms of simulation speed-up, model accuracy and property preservation. The applicability of each technique for real-time applications, particularly in the context of xEV (grid connected electric vehicle) thermal management, together with pros and cons of each method is discussed.
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McGahan, P., Rouaud, C., and Booker, M., "A Comparison of Model Order Reduction Techniques for Real-Time Battery Thermal Modelling," SAE Technical Paper 2019-01-0503, 2019, https://doi.org/10.4271/2019-01-0503.Data Sets - Support Documents
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References
- Boulanger , A.G. , Chu , A.C. , Maxx , S. , and Waltz , D.L. Vehicle Electrification: Status and Issues Proceedings of the IEEE 99 6 1116 1138 2011
- Shi , Y. , Smith , K. , Wood , E. , and Pesaran , A. A Multi-Node Thermal System Model for Lithium-Ion Battery Packs American Control Conference (ACC) 2015 IEEE 2015 723 727
- Santini , D.J. , Zhou , Y. , and Werpy , M. R. 2015
- Wilkins , S. , van Sterkenburg S.W.P. , Hoedemaekers E.R.G. , Bogdan Rosca B. et al. Model Identification for Thermal Modelling of a Battery Pack EVS30 Symposium 2017
- Samba , A. 2015
- Shabani , B. and Biju , M. Theoretical Modelling Methods for Thermal Management of Batteries Energies 8 9 10153 10177 2015
- Murashko , K. , Wu , H. , Pyrhönen , J. , and Laurila , L. Modelling of the Battery Pack Thermal Management System for Hybrid Electric Vehicles Power Electronics and Applications (EPE'14-ECCE Europe), 2014 16th European Conference on IEEE 2014 1 10
- Coman , P.T. 2017
- Sato , N. Thermal Behavior Analysis of Lithium-Ion Batteries for Electric and Hybrid Vehicles Journal of Power Sources 99 1-2 70 77 2001
- Pesaran , A.A. , Burch , S. , and Keyser , M. An Approach for Designing Thermal Management Systems for Electric and Hybrid Vehicle Battery Packs 4th Vehicle Thermal Management Systems 1999 24 27
- Markel , T. , Brooker , A. , Hendricks , T. , Johnson , V. et al. ADVISOR: A Systems Analysis Tool for Advanced Vehicle Modeling Journal of Power Sources 110 2 255 266 2002
- Pesaran , A.A. Battery Thermal Models for Hybrid Vehicle Simulations Journal of Power Sources 110 2 377 382 2002
- Johnson , V. , Pesaran , A.A. , and Sack , T. 2001
- Park , C. and Jaura , A.K. Dynamic Thermal Model of Li-Ion Battery for Predictive Behavior in Hybrid and Fuel Cell Vehicles SAE Technical Paper 2003-01-2286 2003 10.4271/2003-01-2286
- Nelson , P. , Dees , D. , Amine , K. , and Henriksen , G. Modeling Thermal Management of Lithium-Ion PNGV Batteries Journal of Power Sources 110 2 349 356 2002
- Neubauer , J. and Wood , E. Thru-Life Impacts of Driver Aggression, Climate, Cabin Thermal Management, and Battery Thermal Management on Battery Electric Vehicle Utility Journal of Power Sources 259 262 275 2014
- Antoulas , A.C. , Ionutiu , R. , Martins , N. , ter Maten , E.J.W. et al. Model Order Reduction: Methods, Concepts and Properties Coupled Multiscale Simulation and Optimization in Nanoelectronics Springer Berlin, Heidelberg 2015 159 265
- Kostetzer , L. and Nallabolu S. System Level Battery Thermal Behaviour Study ANSYS Conference 27. CADFEM Users Meeting 2009
- Gugercin , S. and Antoulas , A.C. A Survey of Model Reduction by Balanced Truncation and Some New Results International Journal of Control 77 8 748 766 2004
- Schilders , W. Introduction to Model Order Reduction Model Order Reduction: Theory, Research Aspects and Applications Berlin, Heidelberg Springer 2008 3 32
- Chen , C.-T. Linear System Theory and Design Oxford University Press, Inc 1998
- Rouaud , C. , Lagonotte , P. , and Alexandre , A. Reduced Models for Temperature Control of a Power Drive with Variable Cooling Fluid Flow IEEE Industrial Electronics, IECON 2006-32nd Annual Conference on IEEE 2006 4806 4812
- Lagonotte , P. , Alexandre , A. , and Rouaud , C. Reduced Thermal Model of a Power IC with Variable Cooling Fluid Flow International Workshop on Thermal Investigations of ICs and Systems 2003 181 191
- Araújo , R.d.A. , Oliveira , A.L.I. , and Meira , S. A Morphological Neural Network for Binary Classification Problems Engineering Applications of Artificial Intelligence 65 12 28 2017
- Phan , L.L. 2010
- Bishop , C.M. Neural Networks for Pattern Recognition Oxford University Press 1995
- Wang , H. , Liu , Y. , Zheng , G. , and Li , G. Temperature Estimation of Power Battery Based on Back Propagation Neural Network 2013
- Kim , T.J. , Youn , B.D. , and Kim , H.J. Battery Pack Temperature Estimation Model for EVs and Its Semi-transient Case Study Chemical Engineering Transactions 33 955 960 2013
- Hu , X.-S. , Sun , F.-C. , Li , S.-B. , and Yang , Y.-L. NARX Modelling of a Lithium Iron Phosphate Battery Used for Electrified Vehicle Simulation International Journal of Modelling, Identification and Control 20 2 181 189 2013
- Rouaud , C. 2004