Based on Energy Router Energy Management Control Strategy in Micro-grid

2022 ◽  
pp. 329-339
Author(s):  
Xuemei Zheng ◽  
Zhongshuai Zhang ◽  
Haoyu Li ◽  
Yong Feng
Keyword(s):  
Energy Management ◽  
Control Strategy ◽  
Management Control ◽  
Micro Grid

Analysis and Control of Torque Split in Hybrid Electric Vehicles by Incorporating Powertrain Dynamics

2018 ◽  
Vol 140 (11) ◽  
Author(s):  
Mehran Bidarvatan ◽  
Mahdi Shahbakhti
Keyword(s):  
Steady State ◽  
Energy Consumption ◽  
Energy Management ◽  
Control Strategy ◽  
Hybrid Electric Vehicle ◽  
Internal Combustion Engines ◽  
Dynamic Models ◽  
Management Control ◽  
Drive Cycle ◽  
Hybrid Electric

Hybrid electric vehicle (HEV) energy management strategies usually ignore the effects from dynamics of internal combustion engines (ICEs). They usually rely on steady-state maps to determine the required ICE torque and energy conversion efficiency. It is important to investigate how ignoring these dynamics influences energy consumption in HEVs. This shortcoming is addressed in this paper by studying effects of engine and clutch dynamics on a parallel HEV control strategy for torque split. To this end, a detailed HEV model including clutch and ICE dynamic models is utilized in this study. Transient and steady-state experiments are used to verify the fidelity of the dynamic ICE model. The HEV model is used as a testbed to implement the torque split control strategy. Based on the simulation results, the ICE and clutch dynamics in the HEV can degrade the control strategy performance during the vehicle transient periods of operation by around 8% in urban dynamometer driving schedule (UDDS) drive cycle. Conventional torque split control strategies in HEVs often overlook this fuel penalty. A new model predictive torque split control strategy is designed that incorporates effects of the studied powertrain dynamics. Results show that the new energy management control strategy can improve the HEV total energy consumption by more than 4% for UDDS drive cycle.

Optimal adaptation equivalent factor of energy management strategy for plug-in CVT HEV

2018 ◽  
Vol 233 (4) ◽  
pp. 877-889 ◽  
Author(s):  
Xinyou Lin ◽  
Qigao Feng ◽  
Liping Mo ◽  
Hailin Li
Keyword(s):  
Energy Management ◽  
Fuel Economy ◽  
Control Strategy ◽  
Hybrid Electric Vehicle ◽  
Adaptation Strategy ◽  
Management Control ◽  
Energy Management Strategy ◽  
Driving Mode ◽  
Driving Cycles ◽  
Equivalent Factor

This study presents an adaptive energy management control strategy developed by optimally adjusting the equivalent factor (EF) in real-time based on driving pattern recognition (DPR), to guarantee the plug-in hybrid electric vehicle (PHEV) can adapt to various driving cycles and different expected trip distances and to further improve the fuel economy performance. First, the optimization model for the EF with the battery state of charge (SOC) and trip distance were developed based on the equivalent consumption minimization strategy (ECMS). Furthermore, a methodology of extracting the globally optimal EF model from genetic algorithm (GA) solution is proposed for the design of the EF adaptation strategy. The EF as the function of trip distances and SOC in various driving cycles is expressed in the form of map that can be applied directly in the corresponding driving cycle. Finally, the algorithm of DPR based on learning vector quantization (LVQ) is established to identify the driving mode and update the optimal EF. Simulation and hardware-in-loop experiments are conducted on synthesis driving cycles to validate the proposed strategy. The results indicate that the optimal adaption EF control strategy will be able to adapt to different expected trip distances and improve the fuel economy performance by up to 13.8% compared to the ECMS with constant EF.

scholarly journals Super Twisting Fractional Order Energy Management Control for a Smart University System Integrated DC Micro-Grid

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 128692-128704
Author(s):  
Yasser Mohammed Alharbi ◽  
Ahmad Aziz Al Alahmadi ◽  
Nasim Ullah ◽  
Habti Abeida ◽  
Mohamed S. Soliman ◽  
...  
Keyword(s):  
Energy Management ◽  
Fractional Order ◽  
Management Control ◽  
University System ◽  
Order Energy ◽  
Micro Grid

Research on Energy Management Control Strategy by dSPACE Based Half-Practicality Simulation

2014 ◽  
Vol 697 ◽  
pp. 263-266
Author(s):  
Qun Zhang Tu ◽  
Xiao Chen Zhang ◽  
Ming Pan ◽  
Xia Feng ◽  
Wei Jie Zheng
Keyword(s):  
Energy Management ◽  
Electric Drive ◽  
Control Strategy ◽  
Management Control ◽  
Drive System ◽  
Hardware In The Loop ◽  
Excellent Performance ◽  
Tracked Vehicle ◽  
Electric Drive System ◽  
Working Efficiency

In order to manage the power of electric drive system effectively and improve the fuel economy and working efficiency of electric drive tracked vehicle, this paper proposed a novel energy management control strategy based on the theory of threshold logic and fuzzy logic. The mathematical models of the key components of electric drive system were built in SIMULINK. To examine and analysis the efficiency of control strategy, a driver-controller based HILS (hardware-in-the-loop simulation) platform was built and the energy management control strategy was verified. The simulation results reveal that the strategy have excellent performance in energy distribution, fuel saving and working efficiency, and the proposed control strategy is simple and easy to realize in a real controller, which provides an effective method for the design and application of energy management control strategy of electric drive tracked vehicle.

Dual Transformerless Single-Stage Current Source Inverter With Energy Management Control Strategy

2013 ◽  
Vol 28 (10) ◽  
pp. 4644-4656 ◽  
Author(s):  
Lucas Sampaio Garcia ◽  
Gustavo Malagoli Buiatti ◽  
Luiz Carlos de Freitas ◽  
Ernane Antônio Alves Coelho ◽  
Valdeir José Farias ◽  
...  
Keyword(s):  
Energy Management ◽  
Control Strategy ◽  
Current Source ◽  
Management Control ◽  
Single Stage ◽  
Current Source Inverter
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