Modeling and model predictive control for hybrid electric vehicles

Minh, Vu Trieu; Rashid, A.

doi:10.1007/s12239-012-0045-0

Cited by 31 publications

(15 citation statements)

References 7 publications

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“…Different to the existing MPC methods about torque coordination control in [15,16], only one model predictive controller is needed and the clutch torque is used as an optimized variable rather than a known parameter to improve the performance of MPC. The idea of MRC in [18] is used for reference in the proposed novel strategy.…”

Section: The Model Predictive Controller Designmentioning

confidence: 99%

“…Koprubasi et al applied switched hybrid theory to the control of a simplified model of a parallel hybrid electric vehicle drivetrain [14]. Minh and Rashid built up a typical model of a parallel hybrid electric vehicle and developed two model predictive controllers for this model to control the speeds and torques for fast clutch engagement [15]. This paper finished the preparation phase for the clutch slipping friction phase but did not involve the control during the clutch slipping friction phase.…”

Section: Introductionmentioning

confidence: 99%

“…The innovations of this paper are outlined as follows. Firstly, only one model predictive controller is needed compared with the existing MPC methods about torque coordination control in [15,16], which is helpful to reduce the computation burden. Secondly, as a pivotal factor, the clutch torque is used as an optimized variable rather than a known parameter in MPC, which will increase the design degree of freedom.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A Novel Torque Coordination Control Strategy of a Single-Shaft Parallel Hybrid Electric Vehicle Based on Model Predictive Control

Sun

Gao

et al. 2015

Mathematical Problems in Engineering

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The torque coordination control during mode transition is a very important task for hybrid electric vehicle (HEV) with a clutch serving as the key enabling actuator element. Poor coordination will deteriorate the drivability of the driver and lead to excessive wearing to the clutch friction plates. In this paper, a novel torque coordination control strategy for a single-shaft parallel hybrid electric vehicle is presented to coordinate the motor torque, engine torque, and clutch torque so that the seamless mode switching can be achieved. Different to the existing model predictive control (MPC) methods, only one model predictive controller is needed and the clutch torque is taken as an optimized variable rather than a known parameter. Furthermore, the successful idea of model reference control (MRC) is also used for reference to generate the set-point signal required by MPC. The parameter sensitivity is studied for better performance of the proposed model predictive controller. The simulation results validate that the proposed novel torque coordination control strategy has less vehicle jerk, less torque interruption, and smaller clutch frictional losses, compared with the baseline method. In addition, the sensitivity and adaptiveness of the proposed novel torque coordination control strategy are evaluated.

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Section: The Model Predictive Controller Designmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A Novel Torque Coordination Control Strategy of a Single-Shaft Parallel Hybrid Electric Vehicle Based on Model Predictive Control

Sun

Gao

et al. 2015

Mathematical Problems in Engineering

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“…A fuzzy adaptive sliding mode approach was applied to the mode transition control in [7], and the switched hybrid theory was applied to the control of a parallel hybrid electric vehicle drivetrain [8]. The model predictive control (MPC) method was also used to manage HEV mode transitions in [9,10], in which two model predictive controllers were needed to accomplish the comfortable transition and synchronize the two drivetrain parts, which were divided by the clutch. Considering the discontinuity of the clutch, a model reference control (MRC) law was proposed to coordinate the engine torque, the clutch torque and the motor torque during the mode transition dynamic process from motor-only mode to compound driving mode [11].…”

Section: Introductionmentioning

confidence: 99%

“…The mechanism modeling is simplified to some extent for the convenience of controller design in the existing research, which is bound to bring about many unmodeled dynamics and a poor control effect. Although a seven-order mathematical model is used in [9,10], the quadratic terms proportional to vehicle speed are neglected in the resistance torque model in order to facilitate the control design; thus, the dynamic characteristics of the HEV powertrain system cannot be precisely described.…”

Section: Introductionmentioning

confidence: 99%

Data-Driven Predictive Torque Coordination Control during Mode Transition Process of Hybrid Electric Vehicles

2017

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Torque coordination control significantly affects the mode transition quality during the mode transition dynamic process of hybrid electric vehicles (HEV). Most of the existing torque coordination control methods are based on the mechanism model, whose control effect heavily depends on the modeling accuracy of the HEV powertrain. However, the powertrain structure is so complex, that it is difficult to establish its precise mechanism model. In this paper, a torque coordination control strategy using the data-driven predictive control (DDPC) technique is proposed to overcome the shortcomings of mechanism model-based control methods for a clutch-enabled HEV. The proposed control strategy is only based on the measured input-output data in the HEV powertrain, and no mechanism model is needed. The conflicting control requirements of comfortability and economy are included in the cost function. The actual physical constraints of actuators are also explicitly taken into account in the solving process of the data-driven predictive controller. The co-simulation results in Cruise and Simulink validate the effectiveness of the proposed control strategy and demonstrate that the DDPC method can achieve less vehicle jerk, faster mode transition and smaller clutch frictional losses compared with the traditional model predictive control (MPC) method.

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Modeling of an Electric Vehicle for Drivability Improvements

Dou

Shi

et al. 2013

Lecture Notes in Electrical Engineering

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Modeling and model predictive control for hybrid electric vehicles

Cited by 31 publications

References 7 publications

A Novel Torque Coordination Control Strategy of a Single-Shaft Parallel Hybrid Electric Vehicle Based on Model Predictive Control

A Novel Torque Coordination Control Strategy of a Single-Shaft Parallel Hybrid Electric Vehicle Based on Model Predictive Control

Data-Driven Predictive Torque Coordination Control during Mode Transition Process of Hybrid Electric Vehicles

Modeling of an Electric Vehicle for Drivability Improvements

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