Survey on Energy Management Strategy for Plug-in Hybrid Electric Vehicles

Wang, Qinpu

doi:10.3901/jme.2017.16.001

Cited by 17 publications

(12 citation statements)

References 1 publication

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“…The minimum equivalent fuel consumption was achieved by reasonably considering the cost of engine power generation and the loss of motor operation. The power consumption and fuel consumption should be treated equivalently, so that the overall fuel consumption is greatly reduced [20].…”

Section: Build Ecms Optimization Objective Functionsmentioning

confidence: 99%

“…The parabolic correction function is written as: The meanings of the variables in formulas (19)- (20) are shown in Table 7.…”

Section: Correction Function With Acceleration a As The Independent Vmentioning

confidence: 99%

“…The meanings of the variables in Formulas (19)- (20) are shown in Table 7. The upper limit of acceleration (m/s 2 ) T emin (ω e (t)) 1 the minimum torque of the engine when the rotating speed is ω e (t)(Nm) a l the lower limit of acceleration (m/s 2 ) T emax (ω e (t)) 1 the maximum torque of the engine when the rotating speed is ω e (t)(Nm) P(aa) correction factor of the vehicle acceleration T mmin (ω m (t)) 1 the minimum torque of the motor when the rotating speed is ω m (t)(Nm) δ,γ acceleration correction function coefficients T mmax (ω m (t)) 1 the maximum torque of the motor when the rotating speed is ω m (t) The final battery equivalent fuel consumption equation is:…”

Section: Establishment Of Equivalence Factor Map With Soc and A As Inmentioning

confidence: 99%

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Minimum Energy Management Strategy of Equivalent Fuel Consumption of Hybrid Electric Vehicle Based on Improved Global Optimization Equivalent Factor

2019

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A parallel hybrid electric vehicle (PHEV) is used to investigate the fuel economy effect of the equivalent fuel consumption minimization strategy (ECMS) with the equivalent factor as the core, where the equivalent factor is the conversion coefficient between fuel thermal energy and electric energy. In the conventional ECMS strategy, the battery cannot continue to discharge when the state of charge (SOC) is lower than the target value. At this time, the motor mainly works in the battery charging mode, making it difficult to adjust the engine operating point to the high-efficiency zone during the acceleration process. To address this problem, a relationship model of the battery SOC, vehicle acceleration a, and equivalent factor S was established. When the battery SOC is lower than the target value and the vehicle demand torque is high, which makes the engine operating point deviate from the high-efficiency zone, the time that the motor spends in the power generation mode during the driving process is reduced. This enables the motor to drive the vehicle at the appropriate time to reduce the engine output torque, and helps the engine operate in the high-efficiency zone. The correction function under US06 condition was optimized by genetic algorithm (GA). The best equivalent factor MAP was obtained with acceleration a and battery SOC as independent variables, and the improved global optimal equivalent factor of ECMS was established and simulated offline. Simulation results show that compared with conventional ECMS, the battery still has positive power output even when the SOC is less than the target value. The SOC is close to the target value after the cycle condition, and fuel economy improved by 1.88%; compared with the rule-based energy management control strategies, fuel economy improved by 10.17%. These results indicate the effectiveness of the proposed energy management strategy.

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Section: Build Ecms Optimization Objective Functionsmentioning

confidence: 99%

“…The parabolic correction function is written as: The meanings of the variables in formulas (19)- (20) are shown in Table 7.…”

Section: Correction Function With Acceleration a As The Independent Vmentioning

confidence: 99%

Section: Establishment Of Equivalence Factor Map With Soc and A As Inmentioning

confidence: 99%

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Minimum Energy Management Strategy of Equivalent Fuel Consumption of Hybrid Electric Vehicle Based on Improved Global Optimization Equivalent Factor

2019

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“…As the core technology of HEVs, the energy management strategy (EMS) directly affects the economy, power perfor- mance, driving performance, and reliability of the vehicle. The EMS solves the problem of energy distribution between different power sources (Wang et al, 2017a;Hannan et al, 2014). According to the state of charge (SOC), the driver's pedal signal, the characteristics of the ICE and the EM, and the power demand of the vehicle, the power or torque distribution of each power source is solved to improve the fuel economy of the vehicle (Sulaiman et al, 2015;Zhao and Guo, 2016).…”

Section: Introductionmentioning

confidence: 99%

Review article: A comprehensive review of energy management strategies for hybrid electric vehicles

Zhu

Liu

et al. 2022

Mech. Sci.

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Abstract. In order to prevent the aggravation of global environmental problems, all industries are facing the challenge of green development. In the automotive field, the development of “new-energy vehicles” (plug-in electric vehicles) is particularly necessary. Hybrid electric vehicles (HEVs) have been proven to be an efficient way of solving environmental and energy problems. As the core of HEVs, the energy management strategy (EMS) plays an important role in fuel economy, power performance, and drivability. However, considering the randomness of actual driving conditions, there are great challenges involved in the establishment of an EMS. Therefore, it is critical to develop an efficient and adaptable EMS. This paper presents a systematic review of EMSs for HEVs. First, different issues that can affect the performance of EMSs are summarized. Second, recent studies on EMSs for HEVs are reviewed. Third, the advantages and disadvantages of different categories of EMSs are compared in detail. Finally, promising EMS research topics for future study are put forward.

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“…The main means of PHEV control is to use energy management strategies (EMS) to meet the driver's power requirements and limit the short-term power consumption of the battery within a certain range, so as to minimize the overall fuel consumption of the vehicle [9]. The rule-based and optimal energy management strategy are the main energy management strategy of plug-in hybrid electric vehicle [10]. In references [11,12], rule-based energy management strategy for PHEV is introduced in detail, such as charge depleting-charge sustaining strategy (CD-CS) [13], etc.…”

Section: Introductionmentioning

confidence: 99%

Research on Energy Management Method of Plug-In Hybrid Electric Vehicle Based on Travel Characteristic Prediction

Wang

Sun

2021

Energies

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In the research on energy management methods of plug-in hybrid electric vehicles, it is expected that a future trend will be to optimize energy management using the information provided by the global positioning system (GPS) and intelligent transportation system (ITS), which is relatively scarce in current research. This study proposes a PHEV energy management method based on travel characteristic prediction. Firstly, this study processes the historical travel data of a certain driver obtained by GPS and ITS and uses the established Markov trajectory prediction model based on key points to predict the trajectory and mileage. Then, on the basis of characteristics analysis of historical travel data, while considering traffic information to form a target cycle, the driving cycles are classified and identified based on traffic information predictions. Then, according to the reasonable SOC allocation range of the four typical cycles, the planning algorithm of the SOC reference trajectory is determined and verified. Finally, based on the previous work, an A-ECMS energy management method based on travel characteristic prediction is established. By comparing different energy management methods, the developed energy management method based on travel characteristic prediction can reasonably utilize power batteries. The fuel saving is about 8.95% higher than the rule-based energy management method, which can effectively improve the whole vehicle’s fuel economy and optimization ability.

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Survey on Energy Management Strategy for Plug-in Hybrid Electric Vehicles

Cited by 17 publications

References 1 publication

Minimum Energy Management Strategy of Equivalent Fuel Consumption of Hybrid Electric Vehicle Based on Improved Global Optimization Equivalent Factor

Minimum Energy Management Strategy of Equivalent Fuel Consumption of Hybrid Electric Vehicle Based on Improved Global Optimization Equivalent Factor

Review article: A comprehensive review of energy management strategies for hybrid electric vehicles

Research on Energy Management Method of Plug-In Hybrid Electric Vehicle Based on Travel Characteristic Prediction

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