In the current scenario, where environmental concern determines the evolution of passenger cars, hybrid electric vehicles (HEV) represent a hub in the automotive sector to reach net-zero CO2 emissions. To fully exploit the energy conversion potential of advanced powertrains, proper energy management strategies are mandatory. In this work, a simulation study is presented, aiming at developing a new control strategy for a P3 parallel plug-in HEV (PHEV). The simulation model is built on MATLAB/Simulink. The proposed strategy is based on an alternative utilization of the thermal engine and electric motor to provide the vehicle power demand (efficient thermal/electric skipping strategy (ETESS)). An adaptive function is then introduced to develop a charge-blended control strategy. Fuel consumption along different driving cycles is evaluated by applying the novel adaptive-ETESS (A-ETESS). To have a proper comparison, the same adaptive function is built on the equivalent consumption minimization strategy (ECMS). Processor-in-the-loop (PIL) simulations are performed to benchmark the A-ETESS. Simulation results highlighted that the proposed strategy provides for a fuel economy similar to ECMS (worse of about 2.5% on average) and a computational effort reduced by 99% on average, opening the possibility of real-time on-vehicle applications.

Assessment of an Adaptive Efficient Thermal/Electric Skipping Control Strategy for the Management of a Parallel Plug-In Hybrid Electric Vehicle

Piras, M.;
2022

Abstract

In the current scenario, where environmental concern determines the evolution of passenger cars, hybrid electric vehicles (HEV) represent a hub in the automotive sector to reach net-zero CO2 emissions. To fully exploit the energy conversion potential of advanced powertrains, proper energy management strategies are mandatory. In this work, a simulation study is presented, aiming at developing a new control strategy for a P3 parallel plug-in HEV (PHEV). The simulation model is built on MATLAB/Simulink. The proposed strategy is based on an alternative utilization of the thermal engine and electric motor to provide the vehicle power demand (efficient thermal/electric skipping strategy (ETESS)). An adaptive function is then introduced to develop a charge-blended control strategy. Fuel consumption along different driving cycles is evaluated by applying the novel adaptive-ETESS (A-ETESS). To have a proper comparison, the same adaptive function is built on the equivalent consumption minimization strategy (ECMS). Processor-in-the-loop (PIL) simulations are performed to benchmark the A-ETESS. Simulation results highlighted that the proposed strategy provides for a fuel economy similar to ECMS (worse of about 2.5% on average) and a computational effort reduced by 99% on average, opening the possibility of real-time on-vehicle applications.
2022
Istituto di Scienze e Tecnologie per l'Energia e la Mobilità Sostenibili - STEMS
hybrid powertrain; optimization strategy; computational efficiency; energy management; fuel economy
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/535820
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