Design and Simulation of an Intelligent Power Management Strategy and a Gearshifting Pattern for Parallel Hybrid Electric Vehicles
,
M.Sc. Thesis
Sharif University of Technology
;
Saadat Foumani, Mahmoud
(Supervisor)
;
Salarieh, Hassan
(Supervisor)
Abstract
A well-designed Control Strategy (CS) in Hybrid Electric Vehicles (HEVs), as the manager of energy flow, reduces the fuel consumption and/or air pollution, while keeps an eye for prolonging the components lifetime. In this regard, the present thesis provides a new CS for parallel HEVs, based on emotional learning. It is noteworthy that the controller consists of a Takagi-Sugeno-Kang (TSK) fuzzy system and a critic. The driver’s torque command, State of Charge (SOC) error, Internal Combustion Engine (ICE) brake torque error and its time derivative constitute the controller inputs, while the output is the ICE torque command. The critic produces two stress signals based on HEV’s battery and ICE...
Cataloging brief
Design and Simulation of an Intelligent Power Management Strategy and a Gearshifting Pattern for Parallel Hybrid Electric Vehicles
,
M.Sc. Thesis
Sharif University of Technology
;
Saadat Foumani, Mahmoud
(Supervisor)
;
Salarieh, Hassan
(Supervisor)
Abstract
A well-designed Control Strategy (CS) in Hybrid Electric Vehicles (HEVs), as the manager of energy flow, reduces the fuel consumption and/or air pollution, while keeps an eye for prolonging the components lifetime. In this regard, the present thesis provides a new CS for parallel HEVs, based on emotional learning. It is noteworthy that the controller consists of a Takagi-Sugeno-Kang (TSK) fuzzy system and a critic. The driver’s torque command, State of Charge (SOC) error, Internal Combustion Engine (ICE) brake torque error and its time derivative constitute the controller inputs, while the output is the ICE torque command. The critic produces two stress signals based on HEV’s battery and ICE...
Find in contentBookmark |
|