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Calibrating a Real-time Energy Management for a Heavy-Duty Fuel Cell Electrified Truck towards Improved Hydrogen Economy
Technical Paper
2022-37-0014
ISSN: 0148-7191, e-ISSN: 2688-3627
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English
Abstract
Fuel cell electrified powertrains are currently a promising technology towards decarbonizing the heavy-duty transportation sector. In this context, extensive research is required to thoroughly assess the hydrogen economy potential of fuel cell heavy-duty electrification. This paper proposes a real-time capable energy management strategy (EMS) that can achieve improved hydrogen economy for a fuel cell electrified heavy-duty truck. The considered heavy-duty truck is modelled first in Simulink® environment. A baseline heuristic map-based controller is then retained that can instantaneously control the electrical power split between fuel cell system and the high-voltage battery pack of the heavy-duty truck. Particle swarm optimization (PSO) is consequently implemented to optimally tune the parameters of the considered EMS. For the aim of this study, the calibration optimization objective involves minimizing the hydrogen consumption estimated by simulating the heavy-duty truck in the Simulink® model. Simulations entail different driving missions, some of which have been generated by using the VECTO software, i.e. the tool used in Europe to certify the CO2 emissions of new heavy-duty vehicles. Furthermore, dynamic programming (DP) is implemented as an off-line reference EMS approach that can identify the global optimal control trajectory over time by knowing the entire driving mission in advance. The real-time EMS calibrated by means of PSO is demonstrated achieving remarkable hydrogen saving potential, which results being only around 5% worse compared with the global optimal benchmark provided by DP.
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Citation
Anselma, P., Spano, M., Capello, M., Misul, D. et al., "Calibrating a Real-time Energy Management for a Heavy-Duty Fuel Cell Electrified Truck towards Improved Hydrogen Economy," SAE Technical Paper 2022-37-0014, 2022.Also In
References
- Ragon , P.L. , and Rodriguez , F. 2 2 2021
- Depcik , C. , Gaire , A. , Gray , J. , Hall , Z. et al. Electrifying Long-Haul Freight—Part II: Assessment of the Battery Capacity SAE Int. J. Commer. Veh. 12 2 2019 87 102
- Yazdani , A. and Bidarvatan , M. Real-Time Optimal Control of Power Management in a Fuel Cell Hybrid Electric Vehicle: A Comparative Analysis SAE Int. J. Alt. Power. 7 1 2018 43 54
- Wu , D. , and Williamson , S.S. Status Review of Power Control Strategies for Fuel Cell Based Hybrid Electric Vehicles 2007 IEEE Canada Electrical Power Conference 218 223 2007
- Sarioglu , I.L. , Klein , O.P. , Schroder , H. , and Kucukay , F. Energy Management for Fuel-Cell Hybrid Vehicles Based on Specific Fuel Consumption due to Load Shifting IEEE Transactions on Intelligent Transportation Systems 13 4 2012 1772 1781
- Shen , D. , Lim , C.C. , and Shi , P. Fuzzy Model Based Control for Energy Management and Optimization in Fuel Cell Vehicles IEEE Transactions on Vehicular Technology 69 12 2020 14674 14688
- Verbruggen , F.J.R. , Silvas , E. , and Hofman , T. Electric Powertrain Topology Analysis and Design for Heavy-Duty Trucks Energies 13 10 2020 2434
- Berr , F. , Abdelli , A. , Postariu , D. , and Benlamine , R. Design and Optimization of Future Hybrid and Electric Propulsion Systems: An Advanced Tool Integrated in a Complete Workflow to Study Electric Devices Oil & Gas Science and Technology 67 2012 547 562
- Anselma , P.G. and Belingardi , G. Fuel Cell Electrified Propulsion Systems for Long-Haul Heavy-Duty Trucks: Present and Future Cost-Oriented Sizing Applied Energy 2021
- Bernard , J. , Delprat , S. , Buchi , F.N. , and Guerra , T.M. Fuel-Cell Hybrid Powertrain: Toward Minimization of Hydrogen Consumption IEEE Transactions on Vehicular Technology 58 7 2009 3168 3176
- Lias , S.G. et al. Ion Energetics Data in NIST Chemistry WebBook, NIST Standard Reference Database Number 69 Gaithersburg MD National Institute of Standards and Technology 2018
- Anselma , P.G. and Belingardi , G. Multi-Objective Optimal Computer-Aided Engineering of Hydraulic Brake Systems for Electrified Road Vehicles Vehicle System Dynamics 60 2 2022 391 412
- Guezennec , Y. , Choi , T.-Y. , Paganelli , G. , and Rizzoni , G. Supervisory Control of Fuel Cell Vehicles and Its Link to Overall System Efficiency and Low-Level Control Requirements Proceedings of the 2003 American Control Conference 3 2003 2055 2061
- Kandidayeni , M. , Macias , A. , Boulon , L. , and Kelouwanic , S. Investigating the Impact of Ageing and Thermal Management of a Fuel Cell System on Energy Management Strategies Applied Energy 274 2020 115293
- Bellman , R. and Lee , E. History and development of dynamic programming IEEE Control Systems Magazine 4 4 1984 24 28
- Xu , L. , Mueller , C.D. , Li , J. , Ouyang , M. et al. Multi-Objective Component Sizing Based on Optimal Energy Management Strategy of Fuel Cell Electric Vehicles Applied Energy 157 2015 664 674
- Miretti , F. , Misul , D. , and Spessa , E. DynaProg: Deterministic Dynamic Programming Solver for Finite Horizon Multi-Stage Decision Problems SoftwareX 14 2021 100690
- Sundstrom , O. , and Guzzella , L. A Generic Dynamic Programming Matlab Function 2009 IEEE Control Applications, (CCA) & Intelligent Control, (ISIC) 2009 1625 1630
- Elbert , P. , Ebbesen , S. , and Guzzella , L. Implementation of Dynamic Programming for $n$-Dimensional Optimal Control Problems with Final State Constraints IEEE Transactions on Control Systems Technology 21 3 2013 924 931
- Feroldi , D. , Serra , M. , and Riera , J. Energy Management Strategies based on efficiency map for Fuel Cell Hybrid Vehicles J. Power Sources 190 2 2009 387 401 10.1016/j.jpowsour.2009.01.040
- Kennedy , J. , and Eberhart , R. Particle Swarm Optimization Proceedings of ICNN’95 - International Conference on Neural Networks, 1942-1948 4 1995 10.1109/ICNN.1995.488968
- Liimatainen , H. , Van Vliet , O. , and Aplyn , D. The Potential of Electric Trucks-An International Commodity-Level Analysis Applied Energy 236 2019 804 814
- Southwest Research Institute 2022 https://www.swri.org/press-release/low-load-cycle-llc-heavy-duty-diesel-engine-emissions
- Zacharof , N.G. and Fontaras , G. Report on VECTO Technology Simulation Capabilities and Future Outlook Luxembourg Publications Office of the European Union 2016