Multihorizon Model Predictive Control: An Application to Integrated Power and Thermal Management of Connected Hybrid Electric Vehicles
IEEE Transactions on Control Systems Technology(2022)
摘要
In this article, we propose a multihorizon model predictive control (MH-MPC) approach with applications to integrated power and thermal management (iPTM) of connected hybrid electric vehicles (HEVs). The proposed MH-MPC leverages preview and optimization over a short receding and a long shrinking horizon, where the accuracy of preview, model, and integration can be different over different horizons. Compared with a conventional MPC-based approach with a short prediction horizon and terminal cost, the MH-MPC improves fuel consumption to a level comparable to dynamic programming (DP) while still being computationally affordable. A statistical sensitivity analysis over real-world city driving cycles is conducted to demonstrate the robustness of MH-MPC to moderate levels of uncertainty in the long-term preview.
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关键词
Model predictive control (MPC),multitimescale optimization,power and thermal management (PTM)
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