Research on instantaneous optimal control of the hybrid electric vehicle with planetary gear sets

Wang, Shaohua; Zhang, Sheng; Shi, Dehua; Sun, Xiaoyun; He, Jianqiang

doi:10.1007/s40430-018-1550-5

Cited by 12 publications

(5 citation statements)

References 33 publications

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“…There are several works that fail to provide any kind of online validation of their EMS' performance. After the review, the following approaches were identified for this purpose: HIL simulation platform based on dSPACE real-time simulator [24,26], non-commercial HIL test benches [31,40], measuring the elapsed time of simulations and checking if they fit for real-time operation [30,32,38,42,46] and driver-in-the-loop (DIL) using the IPG Carmaker platform [37].…”

Section: Discussionmentioning

confidence: 99%

“…The results confirmed the effectiveness of the proposed control strategy but it was commented that, under other working conditions, the fuel-saving results would change. Wang et al [24] proposed an adaptive law that updated the equivalence factor of the ECMS according to the vehicle state. The authors focused on the ease of implementing the adaptive law in real time and conducted hardware in the loop simulations in dSPACE to validate their EMS.…”

Section: Ecms Emssmentioning

confidence: 99%

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Analyzing the Improvements of Energy Management Systems for Hybrid Electric Vehicles Using a Systematic Literature Review: How Far Are These Controls from Rule-Based Controls Used in Commercial Vehicles?

et al. 2020

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The hybridization of vehicles is a viable step toward overcoming the challenge of the reduction of emissions related to road transport all over the world. To take advantage of the emission reduction potential of hybrid electric vehicles (HEVs), the appropriate design of their energy management systems (EMSs) to control the power flow between the engine and the battery is essential. This work presents a systematic literature review (SLR) of the more recent works that developed EMSs for HEVs. The review is carried out subject to the following idea: although the development of novel EMSs that seek the optimum performance of HEVs is booming, in the real world, HEVs continue to rely on well-known rule-based (RB) strategies. The contribution of this work is to present a quantitative comparison of the works selected. Since several studies do not provide results of their models against commercial RB strategies, it is proposed, as another contribution, to complete their results using simulations. From these results, it is concluded that the improvement of the analyzed EMSs ranges roughly between 5% and 10% with regard to commercial RB EMSs; in comparison to the optimum, the analyzed EMSs are nearer to the optimum than commercial RB EMSs.

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Section: Discussionmentioning

confidence: 99%

Section: Ecms Emssmentioning

confidence: 99%

Analyzing the Improvements of Energy Management Systems for Hybrid Electric Vehicles Using a Systematic Literature Review: How Far Are These Controls from Rule-Based Controls Used in Commercial Vehicles?

et al. 2020

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“…Using a globally optimal control method based on the dynamic programming (DP) technique, Hu [13] simulated the best economic scenario and the best power performance of the configuration scheme generated for their proposed single-row star-row split hybrid powertrain configuration design scheme. Wang [14] established a transient optimal control to regulate the power flow of a power-split hybrid vehicle with a dual planetary gear set as the focus. Lin [15] proposed a mechatronic model for an HEV powertrain and investigated the control of electric motors in the powertrain, and the results show that electric motors are not only meaningful for improving the comfort of the vehicle but also for reducing the fatigue life loss of planetary gear sets both in pure electric vehicle mode and in hybrid vehicle mode.…”

Section: Introductionmentioning

confidence: 99%

Power-Split Hybrid Train Configuration Design Based on a Single-Row Star Row

Li¹,

Zhang

Qu³

et al. 2023

Applied Sciences

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The fundamental component of a hybrid train system is the hybrid power-coupling mechanism. This paper proposes a single-row star-row power-split arrangement for the power-coupling method in a hybrid train. In order to create input and output power-split configuration schemes for a hybrid train power mechanism, a graphical–theoretical model and a relationship matrix were first established. An electromechanical path power proportion equation was then established to filter out two input power-split configurations. The working states of three developed hybrid power-coupling mechanism schemes were studied to find the scheme that fulfills hybrid train design criteria to meet the power, operating mode, and spatial structural arrangement requirements. Finally, by creating a simulation model for the entire vehicle, the dynamics, battery state of charge (SOC) value, and overall vehicle efficiency for the configuration were simulated and examined. The findings demonstrate that the single-row star-row power-split design technique presented here significantly enhances the train performance.

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“…The related strategy can be called equivalent consumption minimization strategy (ECMS). 11 The main challenge for implementing ECMS is the estimation of EF. 12 Optimal constant EF can gain near global optimal results and simplify the application of ECMS, but it demonstrates poor adaptability for different conditions.…”

Section: Introductionmentioning

confidence: 99%

Adaptive energy management strategy for hybrid electric vehicle based on power prediction

Shi

XiangWei

Wang

et al. 2022

Proceedings of the Institution of Mechanical Engineers, Part D:

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The advantages of hybrid electric vehicle (HEV) in energy-saving strongly rely on the energy management strategy. Equivalent consumption minimization strategy (ECMS) is one kind of well-known instantaneous strategies with the capability of online application. Due to the complicated driving conditions, there are some limitations for the application of ECMS with fixed equivalence factor (EF). Therefore, the adaptive ECMS (A-ECMS) based on the average predicted power is proposed and studied. The average power is predicted by a polynomial function with the average velocity and average acceleration as prediction inputs. The coefficients of the prediction model are updated by the recursive least squares algorithm. By investigating the impacts of different power requirements and EF on the battery charging/discharging behaviors, the explicit expression model of adaptive EF based on the average predicted power and battery SOC is established. The particle swarm optimization (PSO) method is further adopted to derive the parameters of the explicit expression model. Simulation results demonstrate that when the average power is higher than 0.5 kW, the prediction accuracy of the proposed power prediction model is higher than 91%. Compared with the constant ECMS which uses the corresponding optimal EF under different test cycles, although the equivalent fuel economy with the proposed A-ECMS slightly deteriorates, most of the deterioration is smaller than 5%, while the battery charging sustainability for all test cycles are well maintained. The proposed strategy ensures good cycle adaptability in achieving good fuel economy and battery charging sustainability.

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Research on instantaneous optimal control of the hybrid electric vehicle with planetary gear sets

Cited by 12 publications

References 33 publications

Analyzing the Improvements of Energy Management Systems for Hybrid Electric Vehicles Using a Systematic Literature Review: How Far Are These Controls from Rule-Based Controls Used in Commercial Vehicles?

Analyzing the Improvements of Energy Management Systems for Hybrid Electric Vehicles Using a Systematic Literature Review: How Far Are These Controls from Rule-Based Controls Used in Commercial Vehicles?

Power-Split Hybrid Train Configuration Design Based on a Single-Row Star Row

Adaptive energy management strategy for hybrid electric vehicle based on power prediction

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