Hybrid Electric Vehicle Two-Step Fuel Efficiency Optimization With Decoupled Energy Management and Speed Control

Abstract

Hybrid electric vehicles (HEVs) offer an effective solution for emissions reduction and fuel energy savings. The pursuit of further improvements in their energy efficiency has led to the two fundamental optimization challenges of vehicle speed and powertrain energy management (EM), which are inherently coupled. This paper examines the vehicle speed and powertrain EM co-optimization problem for fuel economy for a series HEV following a prescribed route with expected traveling time. In order to overcome the computational burden of a large scale optimal control problem (OCP), this work presents a novel twostep optimal control strategy that suitably separates the cooptimization problem on the basis of involving the characteristics of the HEV powertrain power split and losses in the speed optimization step without an explicit use of a powertrain model. A benchmark method that simultaneously solves the optimal driving speed and the energy source power split is introduced, which is used to show the solution quality of the proposed approach. It is illustrated that the proposed method yields a driving speed solution close to the benchmark method, and additionally it outperforms the benchmark fuel economy, with much higher computational efficiency. The simplicity and effectiveness of the proposed two-step approach make it a practical and implementable EM control strategy.

Data-driven based eco-driving control for plug-in hybrid electric vehicles

“…The basic driving cycle can showcase the designed velocity profiles and the powertrain operating state by different control strategies, with a larger feasible range of speed planning. Additionally, such a simulation can also provide a reference for identifying the rules during velocity planning, since arbitrary driving cycles can be regarded as the combinations of numerous basic driving cycles [41].…”

Joint Propulsion and Cooling Energy Management of Hybrid Electric Vehicles by Optimal Control

“…The objective of this optimization problem is to find the primary and secondary sources power quantities, P P S and P SS respectively, that minimize the fuel consumption m f (t f ), subject to the powertrain system dynamics (fuel mass (7) and the SOC (19) only) and the algebraic constraint of power balance at the DC link as given by (2) (in this case P V L = P P L ). The problem can be further simplified by utilizing: a) the constraint (2), b) the linear dependence of the fuel consumption rate on the PS power (see (7)), which enables the alternative objective of min t f t0 (P P L − P SS )dt to be used instead of min m f (t f ), and c) t f t0 P P L dt being completely determined by the followed speed profile according to (1) and (6). OCP-EM can thus be simplified to an optimization problem with a single input u = P SS and a single state x = SOC, as follows:…”

“…Therefore, an appropriate energy management (EM) control strategy is required to determine the power sharing between the two energy sources to minimize fuel consumption. Two main types of EM strategies have been developed in the literature: optimization-based and rule-based control strategies [1]- [6]. The optimization-based methods are essentially based on the formulation of an optimal control problem (OCP), which can be solved by numerous optimization tools, including dynamic programming [1], Pontryagin's Minimum Principle [7], [8], model predictive control [9], [10] and equivalent consumption minimization strategy (ECMS).…”

Assessing the Energy Efficiency of an Electric Car

“…These processes are connected to energy losses [1]. Scientific publications, in many cases, pay attention only to particular components of electric cars, mostly to energy efficiency of electric car's batteries [2][3][4], or to efficiency of hybrid vehicles [5][6][7].…”