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This brief proposes a real-time energy management approach for a hybrid tracked vehicle to adapt to different driving conditions. To characterize different route segments online, an onboard learning algorithm for Markov Chain models is employed to generate transition probability matrices of power demand. The induced matrix norm is presented as an initialization criterion to quantify differences between...
To realize the optimal energy allocation between the engine-generator and battery of a hybrid tracked vehicle (HTV), a reinforcement learning-based real-time energy-management strategy was proposed. A systematic control-oriented model for the HTV was built and validated through the test bench, including the battery pack, the engine-generator set (EGS), and the power request. To use effectively the...
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