Effect of engine dynamics on optimal power-split control strategies in hybrid electric vehicles
Paper i proceeding, 2020

This paper presents a model predictive control (MPC) based supervisory power-split control strategy, which optimises fuel and energy consumption in Hybrid Electric Vehicles (HEVs) by incorporating powertrain actuator dynamic models. In HEVs, while distributing the driver demand to the powertrain actuators, a standard approach is to approximate the actuator energy conversion dynamics with steady-state maps, which leads to sub-optimal control policy and increased fuel energy consumption, especially for a driving mission with high transient demands. To address this shortfall, the control strategy proposed in this paper explicitly integrates an experimentally validated dynamic model of gasoline internal combustion engine (ICE) into an MPC based power-split controller. The proposed strategy is validated in a parallel HEV platform, where the sensitivity of the HEV energy consumption w.r.t. its actuator dynamics and the transients in its load demands, is also established. The results enable an understanding of the energy saving potential in HEVs that supports the inclusion of actuator dynamic models in optimal power-split controllers and it also establishes that the proposed control strategy realises higher energy and fuel savings in HEVs.




Fuel consumption

Parallel Hybrid

Dynamic Optimisation

Powertrain Actuator Dynamics

Optimal Strategies

Engine Dynamics


Optimal Energy Management


Anand Ganesan

Chalmers, Elektroteknik, System- och reglerteknik, Reglerteknik

Volvo Cars

Sebastien Gros

Norges teknisk-naturvitenskapelige universitet

Nikolce Murgovski

Chalmers, Elektroteknik, System- och reglerteknik, Mekatronik

Chih Feng Lee

Volvo Cars

Martin Sivertsson

Volvo Cars

2020 IEEE Vehicle Power and Propulsion Conference, VPPC 2020 - Proceedings

9781728189598 (ISBN)

17th IEEE Vehicle Power and Propulsion Conference, VPPC 2020
Virtual, Gijon, Spain,




Annan elektroteknik och elektronik



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