Automated Engine Calibration of Hybrid Electric Vehicles
2015 (English)In: IEEE Transactions on Control Systems Technology, ISSN 1063-6536, E-ISSN 1558-0865, Vol. 23, no 3, p. 1063-1074, article id 6924797Article in journal (Refereed) Published
Abstract [en]
We present a method for automated engine calibration, by optimizing engine management settings and power-split control of a hybrid electric vehicle (HEV). The problem, which concerns minimization of fuel consumption under a NOxconstraint, is formulated as an optimal control problem. By applying Pontryagin's maximum principle, this paper shows that the problem is separable in space. In the case where the limits of battery state of charge are not activated, we show that the optimization problem is also separable in time. The optimal solution is obtained by iteratively solving the power-split control problem using dynamic programming or the equivalent consumption minimization strategy. In addition, we present a computationally efficient suboptimal solution, which aims at reducing the number of power-split optimizations required. An example is provided concerning optimization of engine management settings and power-split control of a parallel HEV.
Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers Inc. , 2015. Vol. 23, no 3, p. 1063-1074, article id 6924797
Keywords [en]
Engine calibration, engine management system, hybrid electric vehicle (HEV), optimal control, Battery management systems, Calibration, Charging (batteries), Dynamic programming, Electric machine control, Engines, Iterative methods, Optimal control systems, Optimization, Power control, Vehicles, Battery state of charge, Computationally efficient, Engine management systems, Optimal control problem, Optimal controls, Optimization problems, Pontryagin's maximum principle, Hybrid vehicles
National Category
Natural Sciences
Identifiers
URN: urn:nbn:se:ri:diva-42418DOI: 10.1109/TCST.2014.2360920Scopus ID: 2-s2.0-85027932788OAI: oai:DiVA.org:ri-42418DiVA, id: diva2:1381304
2019-12-202019-12-202020-12-01Bibliographically approved