Global Approach for Hybrid Vehicle Optimal Control

Abstract

In this paper, we describe the global approach that has been developed at INRETS-LTE for hybrid powertrain sizing, consumption gain evaluation, and optimal control. The procedure is described in the particular case of a two clutch parallel hybrid architecture, but could apply to any other configuration. Firstly the context and the common issues related to this subject are described. Then our global approach is detailed: sizing procedure, offline global optimization process, method for obtaining suboptimal online energy management laws, and the use of these laws on the test bench. Simulation or optimization results are presented at each step of the procedure.

Engine Cooling System Optimization for Fuel Consumption Reduction

“…For optimization purposes, an inverse modeling approach of the vehicle is applied, as described in [2] or [3]. The goal is to determine the necessary engine fuel consumptionṁ f uel as a function of vehicle acceleration, specified vehicle speed v, a and selected gear.…”

Component-in-the-Loop Testing of Automotive Powertrains Featuring All-Wheel-Drive

“…The patent by General Motors [10] used the same principle of a simulated inertia but introduced a more advanced virtual part that included an automatic transmission with a torque converter and a planetary gearbox, as well as a regulator of the virtual vehicle's velocity able of tracking driving cycles by means of engine throttle control. In the works published during the following three decades [11][12][13][14][15][16][17][18][19][20][21][22], the simulated vehicle inertia and virtual powertrain components were used in CiL systems for testing conventional, hybrid [12][13][14][15]19], and electric [16][17][18] powertrains. The evolution of these techniques also has resulted in engine-in-the-loop testing systems [20][21][22] having a wide use in powertrain development.…”

Optimal control of fuel economy in parallel hybrid electric vehicles

“…Simplified system models were used and the effect and component sizes [10,16]. This supplies a of the frequent start-stop of the engine on fuel criterion to evaluate the powertrain optimization consumption was not considered.…”

“…in reference [16] to optimize the energy management This provides a way to evaluate the effectiveness laws. However, the well-known drawback of the DP of optimization in stage 2.…”

“…An [13][14][15][16]. The former two algorithms are based on an analytical system model, which means that approxi-algorithm restricting the exploring region is designed to reduce computational complexity.…”