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Pareto optimal map concept has been applied to the optimization of the vehicle system control (VSC) strategy for a power-split hybrid electric vehicle (HEV) system. The methodology relies on an inner-loop optimization process to define Pareto maps of the best engine and electric motor/generator operating points given wheel power demand, vehicle speed, and battery power. Selected levels of model fidelity, from simple to very detailed, can be used to generate the Pareto maps. Optimal control is achieved by applying Pontryagin's minimum principle which is based on minimization of the Hamiltonian comprised of the rate of fuel consumption and a co-state variable multiplied by the rate of change of battery SOC. The approach delivers optimal control for lowest fuel consumption over a drive cycle while accounting for all critical vehicle operating constraints, e.g. battery charge balance and power limits, and engine speed and torque limits.

Hybrid electric vehicle (HEV) systems offer significant improvements in vehicle fuel economy and reductions in vehicle generated greenhouse gas emissions. The widely accepted power-split HEV system configuration couples together an internal combustion engine with two electric machines (a motor and a generator) through a planetary gear set. This paper describes a methodology for analysis and optimization of alternative HEV power-split configurations defined by alternative connections between power sources and transaxle. The alternative configurations are identified by a matrix of kinematic equations for connected power sources. Based on the universal kinematic matrix, a generic method for automatically formulating dynamic models is developed. Screening and optimization of alternative configurations involves verification of a set of design requirements which reflect: vehicle continuous operation, e.g. grade test; and vehicle dynamic operation such as acceleration and drivability.