Impact of Energy Management Strategy Calibration on Component Degradation and Fuel Economy of Heavy-Duty Fuel Cell Vehicles

[1]  H. Koegeler,et al.  Optimal Calibration of an Adaptive and Predictive Energy Management Strategy for Fuel Cell Electric Trucks , 2022, Energies.

[2]  Stefan Jakubek,et al.  Predictive Battery State of Charge Reference Generation Using Basic Route Information for Optimal Energy Management of Heavy-Duty Fuel Cell Vehicles , 2021, IEEE Transactions on Vehicular Technology.

[3]  D. Hissel,et al.  Hybrid fuel cell system degradation modeling methods: A comprehensive review , 2021 .

[4]  Stefan Jakubek,et al.  Energy management of heavy-duty fuel cell vehicles in real-world driving scenarios: Robust design of strategies to maximize the hydrogen economy and system lifetime , 2021 .

[5]  Gilbert Laporte,et al.  Battery degradation and behaviour for electric vehicles: Review and numerical analyses of several models , 2017 .

[6]  R. Thring,et al.  An Energy Management Strategy to concurrently optimise fuel consumption & PEM fuel cell lifetime in a hybrid vehicle , 2016 .

[7]  S.M.T. Bathaee,et al.  Multi-objective genetic optimization of the fuel cell hybrid vehicle supervisory system: Fuzzy logic and operating mode control strategies , 2015 .

[8]  Ferdinand Panik,et al.  Dynamic programming technique for optimizing fuel cell hybrid vehicles , 2015 .

[9]  K. Ghedamsi,et al.  Energy management and fault tolerant control strategies for fuel cell/ultra-capacitor hybrid electric vehicles to enhance autonomy, efficiency and life time of the fuel cell system , 2015 .

[10]  P. Bauer,et al.  Practical Capacity Fading Model for Li-Ion Battery Cells in Electric Vehicles , 2013, IEEE Transactions on Power Electronics.

[11]  J. Kalita Multi-objective Optimization , 2012 .

[12]  P. Pei,et al.  A quick evaluating method for automotive fuel cell lifetime , 2008 .

[13]  Jean-Michel Vinassa,et al.  A Comprehensive Review on Energy Management Strategies for Electric Vehicles Considering Degradation Using Aging Models , 2021, IEEE Access.