Lars Löwenstein

Deep reinforcement learning based energy management strategy of fuel cell hybrid railway vehicles considering fuel cell aging

Kai Deng, Yingxu Liu, Di Hai et al. · Energy Conversion and Management · 2021 · 151 citations

Engineering, Reinforcement Learning (Computer Engineering), Deep Reinforcement +11

A scalable, causal, adaptive rule-based energy management for fuel cell hybrid railway vehicles learned from results of dynamic programming

Hujun Peng, Jianxiang Li, Andreas Thul et al. · eTransportation · 2020 · 74 citations

Railway Traffic, Engineering, Energy Management +7

An adaptive PMP-based model predictive energy management strategy for fuel cell hybrid railway vehicles

Kai Deng, Hujun Peng, Steffen Dirkes et al. · eTransportation · 2020 · 74 citations

Electrical Engineering, Engineering, Energy Efficiency +9

A scalable, causal, adaptive energy management strategy based on optimal control theory for a fuel cell hybrid railway vehicle

Hujun Peng, Jianxiang Li, Lars Löwenstein et al. · Applied Energy · 2020 · 62 citations

Engineering, Energy Efficiency, Energy Management +10

Offline optimal energy management strategies considering high dynamics in batteries and constraints on fuel cell system power rate: From analytical derivation to validation on test bench

Hujun Peng, Chen Zhu, Jianxiang Li et al. · Applied Energy · 2020 · 41 citations

Electrical Engineering, Energy Control, Engineering +11