scholarly journals Coordinated train control and energy management control strategies

2002 ◽  
Author(s):  
S.P. Gordon ◽  
D.G. Lehrer
Keyword(s):  
Energy Management ◽  
Control Strategies ◽  
Management Control ◽  
Train Control

Real Time Energy Management Control Strategies for an Electrically Supercharged Gasoline Hybrid Vehicle

2020 ◽  
Author(s):  
Francesco Accurso ◽  
Alessandro Zanelli ◽  
Luciano Rolando ◽  
Federico Millo
Keyword(s):  
Real Time ◽  
Energy Management ◽  
Control Strategies ◽  
Hybrid Vehicle ◽  
Management Control

scholarly journals Towards a Smarter Energy Management System for Hybrid Vehicles: A Comprehensive Review of Control Strategies

2019 ◽  
Vol 9 (10) ◽  
pp. 2026 ◽  
Author(s):  
Nan Xu ◽  
Yan Kong ◽  
Liang Chu ◽  
Hao Ju ◽  
Zhihua Yang ◽  
...  
Keyword(s):  
Energy Management ◽  
Control Strategies ◽  
Large Data ◽  
Management Control ◽  
Mode Switching ◽  
Rule Based ◽  
Comprehensive Review ◽  
Main Research ◽  
Deterministic Dynamic ◽  
Management Optimization

This paper presents a comprehensive review of energy management control strategies utilized in hybrid electric vehicles (HEVs). These can be categorized as rule-based strategies and optimization-based strategies. Rule-based strategies, as the most basic strategy, are widely used due to their simplicity and practical application. The focus of rule-based strategies is to determine and optimize the optimal threshold for mode switching; however, they fall into a local optimal solutions. To have better performance in energy management, optimization-based strategies were developed. The categories of the existing optimization-based strategies are identified from the latest literature, and a brief study of each strategy is discussed, which consists of the main research ideas, the research focus, advantages, disadvantages and improvements to ameliorate optimality and real-time performance. Deterministic dynamic programming strategy is regarded as a benchmark. Based on neural network and the large data processing technology, data-driven strategies are put forward due to their approximate optimality and high computational efficiency. Finally, the comprehensive performance of each control strategy is analyzed with respect to five aspects. This paper not only provides a comprehensive analysis of energy management control strategies for HEVs, but also presents the emphasis in the future.

scholarly journals Neural Network- and Fuzzy Control-Based Energy Optimization for the Switching in Parallel Hybrid Two-Wheeler

2021 ◽  
Vol 12 (1) ◽  
pp. 35
Author(s):  
Supriya Kalyankar-Narwade ◽  
Ramesh Kumar Chidambaram ◽  
Sanjay Patil
Keyword(s):  
Neural Network ◽  
Energy Management ◽  
Hybrid Electric Vehicle ◽  
Control Strategies ◽  
Energy Optimization ◽  
Switching Control ◽  
Management Control ◽  
Energy Utilization ◽  
Power Sources ◽  
Two Wheeler

Optimization of a two-wheeler hybrid electric vehicle (HEV) is a typical challenge compared to that for four-wheeler HEVs. Some of the challenges which are particular to two-wheeler HEVs are throttle integration, smooth switching between power sources, add-on weight compensation, efficiency improvisation in traffic, and energy optimization. Two power sources need to be synchronized skillfully for optimum energy utilization. A prominent variant of HEV is that it easily converts conventional scooters into parallel hybrids by “Through-the-Road (TTR)” architecture. This paper focuses on three switching control strategies of HEVs based on the state of charge, fuzzy logic, and neural network. Further, to optimize energy usage, all these control strategies are compared. Energy management control for the TTR model is developed with vehicle parameters in the Simulink environment and simulated using the “World Harmonized Motorcycle Test Cycle” (WMTC) drive cycle. The multivariable input model is presented with a fuzzy rule-based hybrid switching control. A similar system is also modeled with a neural network-based decision control and the observations are tabulated for the fuel economy and energy management. Simulation results show that the neural network-based optimization results in minimal energy consumption among all three hybrid operations.

scholarly journals On Energy Management Control of a PV-Diesel-ESS Based Microgrid in a Stand-Alone Context

Energies ◽  
2018 ◽  
Vol 11 (8) ◽  
pp. 2164 ◽  
Author(s):  
Ahmed Belila ◽  
Mohamed Benbouzid ◽  
El-Madjid Berkouk ◽  
Yassine Amirat
Keyword(s):  
Energy Management ◽  
Power Flow ◽  
Control Strategies ◽  
Real Data ◽  
Management Control ◽  
Diesel Generator ◽  
Mode Control ◽  
Parallel Mode ◽  
Scale Test ◽  
Reduced Scale

This paper deals with the energy management control of a PV-Diesel-ESS-based microgrid in a stand-alone context. In terms of control, an Isolated Mode Control (IMC) strategy based on a resonant regulator is proposed. In Parallel Mode Control (PMC) conditions, the diesel generator (DG) is controlled to operate at its nominal power. In this context, a supervisory algorithm optimizing the power flow between the microgrid’s various components ensures switching between the two modes for different possible scenarios. To prove the effectiveness of the proposed control strategies, the energy management control (EMC) is tested first using a standard state of charge (SOC) profile emulating the microgrid different states. Then real data are used to simulate the load and solar radiations. An experimental validation on a reduced scale test bench is carried out to prove the feasibility and the effectiveness of the proposed energy management control strategies.

scholarly journals Energy Management Control Strategies in The Egyptian Power System.(Dept.E)

2021 ◽  
Vol 18 (3) ◽  
pp. 61-78
Author(s):  
Hassan Younes ◽  
Kamel Yassin ◽  
El-Hussieny Abd-Raboh
Keyword(s):  
Power System ◽  
Energy Management ◽  
Control Strategies ◽  
Management Control

scholarly journals A Predictive Control Strategy for Energy Management in Micro-Grid Systems

Electronics ◽  
2021 ◽  
Vol 10 (14) ◽  
pp. 1666
Author(s):  
Abdellatif Elmouatamid ◽  
Radouane Ouladsine ◽  
Mohamed Bakhouya ◽  
Najib El kamoun ◽  
Khalid Zine-Dine
Keyword(s):  
Energy Storage ◽  
Energy Management ◽  
Predictive Control ◽  
Energy Production ◽  
Storage Systems ◽  
Control Strategies ◽  
Renewable Energy Sources ◽  
Energy Storage Systems ◽  
Control Approach ◽  
Variable Nature

The integration of renewable energy sources (RES) was amplified, during the past decades, in order to tackle the challenges related to energy demands and CO2 increases. Recently, many initiatives have been taken by promoting the deployment and the usage of micro-grids (MG) in buildings, as decentralized systems, for energy production. However, the variable nature of RESs and the limited size of energy storage systems require the deployment of adaptive control strategies for efficient energy balance. In this paper, a generalized predictive control (GPC) strategy is introduced for energy management (EM) in MG systems. Its main objective is to efficiently connect the electricity generators and consumers in order to predict the most suitable actions for energy flow management. In fact, based on energy production and consumption profiles as well as the availability of energy storage systems, the proposed EM will be able to select the best suitable energy source for supplying the building’s loads. It will efficiently manage the usage of energy storage and the utility grid while maximizing RESs power generation. Simulations have been conducted, using real-sitting scenarios, and results are presented to validate the proposed predictive control approach by showing its effectiveness for MG systems control.

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.

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