Study on engine start-stop control strategy for series-parallel hybrid vehicle

Wang, Hongyu; Qiao, Yunqian; Fang, Yong; Li, Zhiming; Zhiqiang, Yuwen

doi:10.1109/icma.2015.7237789

Cited by 4 publications

(2 citation statements)

References 3 publications

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“…Millo et al, 2014). Li and Jiao (2020) proposed a control strategy to fast and smoothly start the engine for a better drivability, Wang et al (2015) proposed a control algorithm for proper engine start and stop while keeping the engine working in the high efficient area, and Ye et al (2019) proposed an engine start control strategy in decreasing the gear lash to reduce the fuel consumption. Almost all the studies focusing on the engine start expose that when the engine is asked to be started, the clutch switches from a disengagement state to an engagement state.…”

Section: Introductionmentioning

confidence: 99%

Model predictive control-based control strategy to reduce driving-mode switching times for parallel hybrid electric vehicle

Song

2020

Transactions of the Institute of Measurement and Control

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Multi-power sources are included in hybrid electrical vehicles, which leads to multi-driving modes co-existing when driving the vehicle. However, the frequent driving mode switching (DMS) will probably need the engine to be started frequently, which can result in extra fuel consumption. So, avoiding unnecessary DMS should be fully considered when designing the control strategy. For solving this problem, a model predictive control (MPC) strategy integrating Markov chain driving intention identification is put forward. First, the component models of the powertrain system are established. Second, according to the real driving cycle data, a driving intention model based on the Markov chain is designed according to the real driving cycle data. Then the MPC-based control strategy aiming at reducing DMS times is proposed by integrating the cost of DMS. Finally, the proposed control strategy is contrasted with three other control strategies to verify its validity in reducing the mode switching times and improving the fuel economy.

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Section: Introductionmentioning

confidence: 99%

Model predictive control-based control strategy to reduce driving-mode switching times for parallel hybrid electric vehicle

Song

2020

Transactions of the Institute of Measurement and Control

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“…Two different power sources (fuel cell system (FCS) and battery or ultra capacitor (UC)) co‐exist in the power‐train structure, so an effective control strategy is vital to managing the power distribution between the two power sources in order to achieve good fuel economy and dynamic performance [5]. Many previous studies examine the power balance control method for hybrid electric vehicles (HEVs) [6–9].…”

Section: Introductionmentioning

confidence: 99%

Power balance control based on full state feedback for a fuel‐cell hybrid electric vehicle

Song

2020

Asian Journal of Control

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A fuel‐cell vehicle (FCV) mainly depends on the fuel‐cell system (FCS) to provide the power to drive the vehicle. A battery is also integrated as the second power source, which has the advantage of high density and quick dynamic response. Since two power sources co‐exist in the vehicle, the control balance of how to distribute the transient power requirement between the FCS and the battery has a great impact on the performance of the FCV. In this paper, the dynamic model of FCS, the battery, the electric motor (EM), and its control unit are first established. Then the parameters in these models are determined by using the least squares method to achieve an analytical description of the power‐train system. According to the FCV model, the power balance control based on the best state feedback is realized. This optimized control is verified over three different typical driving cycles through simulation and a bench experiment. The results show that the balance control has a practical application for FCV in improving the fuel economy and the dynamic performance.

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Development and Validation of Engine Start/Stop Strategy for P2 Hybrid Electric Vehicle

Palwe¹,

Kanjalkar²

2019

Inventive Computation Technologies

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Study on engine start-stop control strategy for series-parallel hybrid vehicle

Cited by 4 publications

References 3 publications

Model predictive control-based control strategy to reduce driving-mode switching times for parallel hybrid electric vehicle

Model predictive control-based control strategy to reduce driving-mode switching times for parallel hybrid electric vehicle

Power balance control based on full state feedback for a fuel‐cell hybrid electric vehicle

Development and Validation of Engine Start/Stop Strategy for P2 Hybrid Electric Vehicle

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