scholarly journals Enery management in Mobile Hydraulics

2013 ◽  
Vol 135 (06) ◽  
pp. S4-S6
Author(s):  
Andrew Alleyne ◽  
Timothy Deppen ◽  
Jonathan Meyer ◽  
Kim Stelson
Keyword(s):  
Energy Management ◽  
Control Strategies ◽  
Management Strategies ◽  
Electrical Power ◽  
Cost Effective ◽  
Transportation Systems ◽  
Fluid Power ◽  
Energy Management Strategy ◽  
Hybrid Powertrain ◽  
Wide Range

This paper explores research into hydraulic hybrids that span a wide range of applications from heavy-duty vehicles, such as city buses, to small passenger vehicles. This case study also highlights the importance of having a well-designed energy management strategy if one is to maximize benefit of the hybrid powertrain. There is potential for hydraulic hybrid vehicles to offer a cost-effective solution to the need for increased efficiency in transportation systems. The high-power density of fluid power makes it a natural choice for energy storage in urban driving environments where there are frequent starts/stops and large acceleration/braking power demands. Because the opportunities and challenges of fluid power are different than those of electrical power, unique control strategies are needed and a summary of common energy management strategies (EMS) design methods for hydraulic hybrids has been presented.

scholarly journals Research on Energy Management Strategies of Extended-Range Electric Vehicles Based on Driving Characteristics

2020 ◽  
Vol 11 (3) ◽  
pp. 54 ◽  
Author(s):  
Yuanbin Yu ◽  
Junyu Jiang ◽  
Zhaoxiang Min ◽  
Pengyu Wang ◽  
Wangsheng Shen
Keyword(s):  
Energy Management ◽  
Electric Vehicles ◽  
Management Strategy ◽  
Control Strategies ◽  
Management Strategies ◽  
Principal Component ◽  
Driving Cycle ◽  
Control Parameters ◽  
Energy Management Strategy ◽  
Extended Range

The extended-range electric vehicle (E-REV) can solve the problems of short driving range and long charging time of pure electric vehicles, but it is necessary to control the engine working points and allocate the power of the energy sources reasonably. In order to improve the fuel economy of the vehicle, an energy management strategy (EMS) that can adapt to the daily driving characteristics of the driver and adjust the control parameters online is proposed in this paper. Firstly, through principal component analysis (PCA) and iterative self-organizing data analysis techniques algorithm (ISODATA) of historical driving data, a typical driving cycle which can describe driving characteristics of the driver is constructed. Then offline optimization of control parameters by adaptive simulated annealing under each typical driving cycle and online recognition of driving cycles by extreme learning machine (ELM) are applied to the adaptive multi-workpoints energy management strategy (A-MEMS) of E-REV. In the end, compared with traditional rule-based control strategies, A-MEMS achieves good fuel-saving and emission-reduction result by simulation verification, and it explores a new and feasible solution for the continuous upgrade of the EMS.

A Hardware-in-the-Loop Platform for a Series Hybrid Powertrain Featuring Two Equivalent Consumption Minimization Strategies

2014 ◽  
Author(s):  
Sara Mohon ◽  
Satadru Dey ◽  
Beshah Ayalew ◽  
Pierluigi Pisu
Keyword(s):  
Energy Management ◽  
Control Strategies ◽  
Management Strategies ◽  
Electrical Energy ◽  
Hardware In The Loop ◽  
Real Time Control ◽  
Hybrid Powertrain ◽  
Time Control ◽  
Equivalence Factor ◽  
And Performance

Hardware-in-the-loop (HIL) platforms enable rapid evaluation of different system configurations and energy management strategies for electrified/hybrid powertrains without building full vehicle prototypes. This paper outlines a HIL platform for a series hybrid powertrain and discusses particular control strategies. The main hardware components of the platform are a gasoline generator, a lead acid battery pack, a bi-directional dc/dc converter, a programmable dc load, strain gauges, and a rotary encoder. Along with these hardware components, a real-time control prototyping system is used to implement energy management strategies and monitor several signals form the HIL platform. The effectiveness and performance of this platform is demonstrated by implementing two versions of the Equivalent Consumption Minimization Strategy (ECMS). The first version uses a constant equivalence factor for weighting the cost of electrical energy storage, while the second version uses an adaptive equivalence factor based on the deviation of battery state of charge (SOC) from a reference SOC.

scholarly journals Transport modeling: An artificial immune system approach

2006 ◽  
Vol 16 (1) ◽  
pp. 3-30
Author(s):  
Dusan Teodorovic ◽  
Jovan Popovic ◽  
Panta Lucic
Keyword(s):  
Immune System ◽  
Real Time ◽  
Traffic Control ◽  
System Approach ◽  
Artificial Immune System ◽  
Control Strategies ◽  
Transportation Systems ◽  
Artificial Immune ◽  
Real Time Traffic ◽  
Wide Range

This paper describes an artificial immune system approach (AIS) to modeling time-dependent (dynamic, real time) transportation phenomenon characterized by uncertainty. The basic idea behind this research is to develop the Artificial Immune System, which generates a set of antibodies (decisions, control actions) that altogether can successfully cover a wide range of potential situations. The proposed artificial immune system develops antibodies (the best control strategies) for different antigens (different traffic "scenarios"). This task is performed using some of the optimization or heuristics techniques. Then a set of antibodies is combined to create Artificial Immune System. The developed Artificial Immune transportation systems are able to generalize, adapt, and learn based on new knowledge and new information. Applications of the systems are considered for airline yield management, the stochastic vehicle routing, and real-time traffic control at the isolated intersection. The preliminary research results are very promising.

Parametric Modeling and Optimal Control of a Combined Heating and Power System With Energy Storage

2020 ◽  
Author(s):  
Claudia Lucia De Pascalis ◽  
Stephanie Stockar
Keyword(s):  
Energy Storage ◽  
Power Systems ◽  
Power System ◽  
Energy Management ◽  
Renewable Energy Sources ◽  
Cost Effective ◽  
Parametric Modeling ◽  
Medium Size ◽  
Energy Management Strategy ◽  
Generation Cost

Abstract Cogeneration is a well-known and cost effective solution for generating power and heat within the same plant, leading to improved overall efficiency and reduced generation cost. Combined heating and power systems can facilitate the penetration of renewable energy sources in medium size applications through the integration of electric and thermal energy storage units. Due to the complexity of the plant as well as significantly variability in power demand and generation, the design and operation of such systems requires a systematic co-optimization of plant and controller for guaranteeing near optimal performance. In this scenario, this paper presents a physics-based parametric modeling approach for the characterization of the main components of a 1MW combined heating and power system that includes renewable sources, electric and thermal storage devices. To demonstrate the model flexibility and potential benefits achieved by an optimal sizing, the system energy management is optimized using Dynamic Programming. The operational costs for different configurations are compared showing that an optimization of the energy management strategy in conjunction with an improved system sizing lead to more than 6% of reduction in the operational cost.

scholarly journals Development of Global Optimization Algorithm for Series-Parallel PHEV Energy Management Strategy Based on Radau Pseudospectral Knotting Method

Energies ◽  
2019 ◽  
Vol 12 (17) ◽  
pp. 3268
Author(s):  
Kegang Zhao ◽  
Jinghao Bei ◽  
Yanwei Liu ◽  
Zhihao Liang
Keyword(s):  
Global Optimization ◽  
Energy Management ◽  
Computational Efficiency ◽  
Management Strategy ◽  
Hybrid Electric Vehicles ◽  
Minimum Principle ◽  
Management Strategies ◽  
Energy Management Strategy ◽  
Pontryagin Minimum Principle ◽  
Component Sizing

The powertrain model of the series-parallel plug-in hybrid electric vehicles (PHEVs) is more complicated, compared with series PHEVs and parallel PHEVs. Using the traditional dynamic programming (DP) algorithm or Pontryagin minimum principle (PMP) algorithm to solve the global-optimization-based energy management strategies of the series-parallel PHEVs is not ideal, as the solution time is too long or even impossible to solve. Chief engineers of hybrid system urgently require a handy tool to quickly solve global-optimization-based energy management strategies. Therefore, this paper proposed to use the Radau pseudospectral knotting method (RPKM) to solve the global-optimization-based energy management strategy of the series-parallel PHEVs to improve computational efficiency. Simulation results showed that compared with the DP algorithm, the global-optimization-based energy management strategy based on the RPKM improves the computational efficiency by 1806 times with a relative error of only 0.12%. On this basis, a bi-level nested component-sizing method combining the genetic algorithm and RPKM was developed. By applying the global-optimization-based energy management strategy based on RPKM to the actual development, the feasibility and superiority of RPKM applied to the global-optimization-based energy management strategy of the series-parallel PHEVs were further verified.

scholarly journals Examination on Classification of EVs and Energy Management Strategies of HEV

2019 ◽  
Vol 9 (1S) ◽  
pp. 261-266
Keyword(s):  
Electric Vehicle ◽  
Energy Management ◽  
Hybrid Electric Vehicle ◽  
Combustion Engine ◽  
Management Strategies ◽  
Transport Sector ◽  
Energy Management Strategy ◽  
Power Sources ◽  
Power Train ◽  
Range Anxiety

In recent days, the demand for petroleum and emission of pollutant gases continuously increase. This necessitates the electrification power train which replaces Internal Combustion Engine (ICE). Despite pure electric vehicles or Battery Electric Vehicle (EV) reduce the greenhouse gas emissions, there are some major hurdles for EVs to overcome before they totally relieve ICE vehicles form transport sector such as range anxiety, battery storage, economic fall down due to automobile industries, etc. This necessitates Hybrid Electric vehicle (HEV) which combines two different power sources to propel the vehicle. One of the challenges in HEV is how to control the power coming from the two different sources such as battery and ICE. The prime goal of an Energy Management Strategy (EMS) is to manage energy flow such that fuel consumption and emissions are minimized without affecting the vehicle’s performance. In this paper, the different structures of power train and energy management strategies are analysed.

scholarly journals Energy Management Strategy for an Autonomous Hybrid Power Plant Destined to Supply Controllable Loads

Sensors ◽  
2022 ◽  
Vol 22 (1) ◽  
pp. 357
Author(s):  
Imene Yahyaoui ◽  
Natalia Vidal de la Peña
Keyword(s):  
Energy Management ◽  
Management Strategy ◽  
Electrical Power ◽  
Climatic Data ◽  
Diesel Generator ◽  
Energy Management Strategy ◽  
Safe Operation ◽  
Power Sources ◽  
Hybrid Power Plant ◽  
Electrical Loads

This paper proposes an energy management strategy (EMS) for a hybrid stand-alone plant destined to supply controllable loads. The plant is composed of photovoltaic panels (PV), a wind turbine, a diesel generator, and a battery bank. The set of the power sources supplies controllable electrical loads. The proposed EMS aims to ensure the power supply of the loads by providing the required electrical power. Moreover, the EMS ensures the maximum use of the power generated by the renewable sources and therefore minimizes the use of the genset, and it ensures that the batteries bank operates into the prefixed values of state of charge to ensure their safe operation. The EMS provides the switching control of the switches that link the plant components and decides on the loads’ operation. The simulation of the system using measured climatic data of Mostoles (Madrid, Spain) shows that the proposed EMS fulfills the designed objectives.

scholarly journals Energy Management System in the Vehicles using Three Level Neuro Fuzzy Logic

2021 ◽  
Vol 3 (3) ◽  
pp. 149-162
Author(s):  
G Ranganathan ◽  
Jennifer S Raj
Keyword(s):  
Fuzzy Logic ◽  
Energy Consumption ◽  
Energy Management ◽  
Hybrid Electric Vehicle ◽  
Control Strategies ◽  
Electrical Energy ◽  
Energy Management Strategy ◽  
Total Energy Consumption ◽  
Supervisory Controller ◽  
Neuro Fuzzy

This paper has proposed a hybrid electric vehicle that uses intelligent energy management strategy to decrease the energy consumption of the vehicle. Here, the total energy consumption of the vehicle is initially modelled and further investigated to reduce the amount of energy used to be identified as a sum of electrical energy provided by consumed fuels and on-board batteries. In particular, an intelligent controller is proposed in this work to execute its ability to decrease the total amount of energy consumed and improve the energy efficiency of the vehicle. A fuzzy system is utilized in an account supervisory controller to decide the appropriate mode of operation for the system. The part of the proposed work involves development of optimal control strategies by using neuro-fuzzy logic. In order to obtain optimal performance, the controllers are used to regulate vehicle subsystems and set points. The biggest advantage of this work is the reduction in energy consumption and their ability to execute the operation online. Simulink/MATLAB is used to simulate and validate the performance of the proposed work under various conditions and under several dataset values.

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