An active observer-based predictive energy management strategy for engine waste heat recovery system

In this paper, energy management of waste heat recovery system has been attacked based on a three-step problem formulation approach. The problem has been formulated into a bilevel programme, where the upper level is designed to optimise the usage of recovered energy and the lower level is arranged to maximise the recovered energy. However, detailed models for real-time decision making cannot be easily obtained. In order to ensure the energy management performance, an active observer named extended state observer is adopted to compensate for static models via online information of the real energy network. The final decision making of the energy management is conducted based on the reconstructed model, which is simpler and more accurate. An energy network constructed by ----- is employed as the research object. Simulation study conducted by GT-SUITE software is used to verify the sub-goals of the problem configuration, including model self-reconstruction capability and fuel-saving potential. For two given testing cycles, simulation results indicate fairly good self-reconstruction capability can be ensured, while considerable fuel-saving capability can be reached comparing with a baseline strategy, indicating the effectiveness of the proposed approach.