Health Management Control Strategy of Tank Storage Based on Artificial Intelligence

2020 ◽  
Author(s):  
Shengli Lv ◽  
Haizheng Zhang ◽  
Feihu Bao
Keyword(s):  
Artificial Intelligence ◽  
Control Strategy ◽  
Health Management ◽  
Management Control ◽  
Tank Storage

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.

Study and Simulation on the Energy Efficiency Management Control Strategy of Ship Based on Clean Propulsion System

2015 ◽  
Author(s):  
Kai Wang ◽  
Xinping Yan ◽  
Yupeng Yuan
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Control Strategy ◽  
Control Strategies ◽  
Management Control ◽  
Propulsion System ◽  
Power Requirement ◽  
Doubly Fed ◽  
System Configurations ◽  
And Control

Nowadays, with the higher voice of ship energy saving and emission reduction, the research on energy efficiency management is particularly necessary. Energy efficiency management and control of ships is an effective way to improve the ship energy efficiency. In this paper, according to the new clean propulsion system configurations of 5000 tons of bulk carrier, the energy efficiency management control strategy of the clean propulsion system is designed based on the model of advanced brushless doubly-fed shaft generator, propulsion system using LNG/diesel dual fuel engine and energy consumption of the main engine for reducing energy consumption. The simulation model of the entire propulsion system and the designed control strategy were designed. The influence of the engine speed on the ship energy efficiency was analyzed, and the feasibility of the energy efficiency management control strategies was verified by simulation using Matlab/Simulink. The results show that the designed strategies can ensure the power requirement of the whole ship under different conditions and improve the ship energy efficiency and reduce CO2 emissions.

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 Real Time Energy Management and Control of Renewable Energy based Microgrid in Grid Connected and Island Modes

Energies ◽  
2019 ◽  
Vol 12 (2) ◽  
pp. 276 ◽  
Author(s):  
Muhammed Worku ◽  
Mohamed Hassan ◽  
Mohamed Abido
Keyword(s):  
Energy Storage ◽  
Real Time ◽  
Control Strategy ◽  
Current Control ◽  
Buck Converter ◽  
Management Control ◽  
Diesel Generator ◽  
Control Scheme ◽  
Real Time Digital Simulator ◽  
System Frequency

An efficient power management control for microgrids with energy storage is presented in this paper. The proposed control scheme increases the reliability and resiliency of the microgrid based on three distributed energy resources (DERs), namely Photovoltaic (PV), battery, and diesel generator with local active loads. Coordination among the DERs with energy storage is essential for microgrid management. The system model and the control strategy were developed in Real Time Digital Simulator (RTDS). Decoupled d-q current control strategy is proposed and implemented for voltage source converters (VSCs) used to interface the PV and battery sources to the AC grid. A dc-dc buck converter with a maximum power point tracking function is implemented to maximize the intermittent energy generation from the PV array. A controller is proposed and employed for both grid connected and island modes of operation. In grid connected mode, the system frequency and voltage are regulated by the grid. During a fault in island mode, the diesel generator controls the system frequency and voltage in isochronous mode. Results based on the real time digital simulator are provided to verify the superiority and effectiveness of the proposed control scheme.

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