Receding Horizon Control for Distributed Energy Management of a Hybrid Heavy-Duty Vehicle with Auxiliaries

Abstract

In this paper, a real-time and distributed solution to Complete Vehicle Energy Management (CVEM) is presented using a receding control horizon in combination with a dual decomposition. The dual decomposition allows the CVEM optimization problem to be solved by solving several smaller optimization problems. The receding horizon control problem is formulated with variable sample intervals, allowing for large prediction horizons with only a limited number of decision variables and constraints. The receding horizon control problem is solved for a case study of a hybrid heavy-duty vehicle, equipped with a high-voltage battery system and a refrigerated semi-trailer. Simulations demonstrate that close to optimal performance in terms of fuel consumption is obtained. The average execution time is 11.4 ms demonstrating that the proposed solution method is indeed real-time implementable.