Design of an integrated energy management strategy for a plug-in hybrid electric bus

Fan, Likang; Zhang, Youtong; Dou, Haishi; Zou, Runnan

doi:10.1016/j.jpowsour.2019.227391

Cited by 38 publications

(18 citation statements)

References 38 publications

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“…The results show that adding the contribution of integral gains can improve the SOC convergence to the reference value. Hence, many researchers employed a PI controller with the feedback of SOC-related parameter, to regulate EF for tracking the predetermined SOC reference of HEVs [33,[55][56][57] and PHEVs [58][59][60][61][62]. The corresponding EF adjustment rule can be formulated as…”

Section: Proportional Integral (Pi) Controlmentioning

confidence: 99%

A survey on key techniques and development perspectives of equivalent consumption minimisation strategy for hybrid electric vehicles

Chen

Liu

et al. 2021

Renewable and Sustainable Energy Reviews

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Section: Proportional Integral (Pi) Controlmentioning

confidence: 99%

A survey on key techniques and development perspectives of equivalent consumption minimisation strategy for hybrid electric vehicles

Chen

Liu

et al. 2021

Renewable and Sustainable Energy Reviews

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“…The PMSM model is established through experiments, in which PMSM motor data that indicate the torque corresponds to different speeds calculated as motor efficiency are measured by the test platform. When PMSM works as a tractor motor, the PMSM power Pm can be calculated by Equation (7). Meanwhile, when the PMSM works as a generator, Pg could be obtained by Equation (8).…”

Section: Power System Modelingmentioning

confidence: 99%

“…Many methods have been studied in the EV control process. The dominant thoughts of energy management can be classified into rule-based EMS and optimization-based EMS [6,7]. The rule-based control strategy is widely used in the vehicle control unit (VCU) for its simplified calculation in VCU.…”

Section: Introductionmentioning

confidence: 99%

Design of Optimized Energy Management Strategy for All-Wheel-Drive Electric Vehicles

2021

Self Cite

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The performance of the all-wheel-drive electric vehicle is inseparable from the energy management strategy (EMS). An outstanding EMS could extend the cycling mileage, coordinating the power output of the battery and exerts the advantage of the motor comprehensively. However, the current EMS has poor performance in real-time, and this paper proposes the dynamic programming coordination strategy (DPCS) to solve the problem. Firstly, the EMS based on a rule-based control strategy (RBCS) is applied in a different driving cycle. Secondly, the dynamic programming algorithm (DP) is proposed in the process. The DPCS cooperated the advantage of RBCS and DP, extracting the boundary parameters along with the demand power and vehicle speed. Finally, the number of motors joined in the driving condition is elucidated and the method obtains the optimal torque split ratio through a partly-known driving cycle. By incorporating the thought of a basis of rules, the DPCS determines the torque of each motor that confirm the motor working in an efficient range that incorporates the mind of dynamic programming. The method is validated through the simulation. The results show that the strategy can significantly improve the mileage of the driving cycle, with comprehensive performance in energy distribution and utilization.

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“…Actually, flexibility of different driving conditions has been a critical factor that impedes optimal PSMSs implemented in real time, and expedites inspiration of some novel methods by integrating the vehicle-environment cooperative control, such as adaptive ECMSs [26,27] and stochastic DP (SDP) [28,29]. By incorporating classification of driving conditions and/or prediction of future velocity into PSMSs, adaptive energy management responding to different conditions is therefore fulfilled prominently; whereas the onboard ability in self-adaptation of driving conditions imposes heavy computation burden on vehicle control unit (VCU), thus indirectly lowering the system efficiency.…”

Section: B Related Work On Power Sources Management Strategiesmentioning

confidence: 99%

“…For automobile industry, electrification brings a promising response. Amongst all the existing choices, connected plug-in hybrid electric vehicles (cPHEVs) have been regarded as one of effective solutions which are equipped with high efficient internal combustion engines (ICEs) and large capacity batteries [3,4]. cPHEVs, one type of evolved PHEVs, are equipped with vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication, holding larger potential in fuel economy improvement.…”

mentioning

confidence: 99%

A novel strategy for power sources management in connected plug-in hybrid electric vehicles based on mobile edge computation framework

Zhang

Guo

Liu

et al. 2020

Journal of Power Sources

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This paper proposes a novel control framework and the corresponding strategy for power sources management in connected plug-in hybrid electric vehicles (cPHEVs). A mobile edge computation (MEC) based control framework is developed first, evolving the conventional on-board vehicle control unit (VCU) into the hierarchically asynchronous controller that is partly located in cloud. Elaborately contrastive analysis on the performance of processing capacity, communication frequency and communication delay manifests dramatic potential of the proposed framework in sustaining development of the cooperative control strategy for cPHEVs.On the basis of MEC based control framework, a specific cooperative strategy is constructed. The novel strategy accomplishes energy flow management between different power sources with incorporation of the active energy consumption plan and adaptive energy consumption management. The method to generate the reference battery state-of-charge (SOC) trajectories in energy consumption plan stage is emphatically investigated, fast outputting reference trajectories that are tightly close to results by global optimization methods. The estimation of distribution algorithm (EDA) is employed to output reference control policies under the specific terminal conditions assigned via the machine learning based method. Finally, simulation results highlight that the novel strategy attains superior performance in real-time application that is close to the offline global optimization solutions.

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Design of an integrated energy management strategy for a plug-in hybrid electric bus

Cited by 38 publications

References 38 publications

A survey on key techniques and development perspectives of equivalent consumption minimisation strategy for hybrid electric vehicles

A survey on key techniques and development perspectives of equivalent consumption minimisation strategy for hybrid electric vehicles

Design of Optimized Energy Management Strategy for All-Wheel-Drive Electric Vehicles

A novel strategy for power sources management in connected plug-in hybrid electric vehicles based on mobile edge computation framework

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