Intelligent energy management for hybrid fuel cell/battery system

2016 ◽  
Vol 35 (5) ◽  
pp. 1850-1864 ◽  
Author(s):  
Moussa Boukhnifer ◽  
Nadir Ouddah ◽  
Toufik Azib ◽  
Ahmed Chaibet
Keyword(s):  
Optimal Control ◽  
Fuel Cell ◽  
Control Theory ◽  
Energy Management ◽  
Optimal Control Theory ◽  
Hybrid Electric Vehicle ◽  
Minimum Principle ◽  
Management Strategies ◽  
Hybrid Architecture ◽  
Content Type

Purpose The purpose of this paper is to propose two energy management strategies (EMS) for hybrid electric vehicle, the power system is an hybrid architecture (fuel cell (FC)/battery) with two-converters parallel configuration. Design/methodology/approach First, the authors present the EMS uses a power frequency splitting to allow a natural frequency decomposition of the power loads and second the EMS uses the optimal control theory, based on the Pontryagin’s minimum principle. Findings Thanks to the optimal approach, the control objectives will be easily achieved: hydrogen consumption is minimized and FC health is protected. Originality/value The simulation results show the effectiveness of the control strategy using optimal control theory in term of improvement of the fuel consumption based on a comparison analysis between the two strategies.

scholarly journals A Real Time Energy Management Strategy for Plug-in Hybrid Electric Vehicles based on Optimal Control Theory

2014 ◽  
Vol 45 ◽  
pp. 949-958 ◽  
Author(s):  
Laura Tribioli ◽  
Michele Barbieri ◽  
Roberto Capata ◽  
Enrico Sciubba ◽  
Elio Jannelli ◽  
...  
Keyword(s):  
Optimal Control ◽  
Control Theory ◽  
Real Time ◽  
Energy Management ◽  
Electric Vehicles ◽  
Optimal Control Theory ◽  
Management Strategy ◽  
Hybrid Electric Vehicles ◽  
Energy Management Strategy ◽  
Hybrid Electric

A predictive energy management for hybrid vehicles based on optimal control theory

2013 ◽  
Author(s):  
Thomas J. Boehme ◽  
Markus Schori ◽  
Benjamin Frank ◽  
Matthias Schultalbers ◽  
Wolfgang Drewelow
Keyword(s):  
Optimal Control ◽  
Control Theory ◽  
Energy Management ◽  
Optimal Control Theory ◽  
Hybrid Vehicles

scholarly journals Applying optimal control theory to complex epidemiological models to inform real-world disease management

2018 ◽  
Author(s):  
E.H. Bussell ◽  
C.E. Dangerfield ◽  
C.A. Gilligan ◽  
N.J. Cunniffe
Keyword(s):  
Optimal Control ◽  
Disease Management ◽  
Control Theory ◽  
Simulation Model ◽  
Optimal Control Theory ◽  
Management Strategies ◽  
Simulation Models ◽  
Open Loop ◽  
Small Subset ◽  
Control Disease

SummaryMathematical models provide a rational basis to inform how, where and when to control disease. Assuming an accurate spatially-explicit simulation model can be fitted to spread data, it is straightforward to use it to test the performance of a range of management strategies. However, the typical complexity of simulation models and the vast set of possible controls mean that only a small subset of all possible strategies can ever be tested. An alternative approach – optimal control theory – allows the very best control to be identified unambiguously. However, the complexity of the underpinning mathematics means that disease models used to identify this optimum must be very simple. We highlight two frameworks for bridging the gap between detailed epidemic simulations and optimal control theory: open-loop and model predictive control. Both these frameworks approximate a simulation model with a simpler model more amenable to mathematical analysis. Using an illustrative example model we show the benefits of using feedback control, in which the approximation and control are updated as the epidemic progresses. Our work illustrates a new methodology to allow the insights of optimal control theory to inform practical disease management strategies, with the potential for application to diseases of plants, animals and humans.

scholarly journals Optimal controller design based on minimum principle

2018 ◽  
Vol 173 ◽  
pp. 01001
Author(s):  
Huang Da ◽  
Huang ShuCai
Keyword(s):  
Optimal Control ◽  
Control Theory ◽  
Optimal Control Theory ◽  
Controller Design ◽  
Minimum Principle ◽  
Adaptive Controller ◽  
Control Effect ◽  
Modern Control Theory ◽  
Important Position ◽  
The Ideal

Optimal control theory is the foundation of the modern control theory, the minimum principle in optimal control theory has a very important position, using the minimum principle to design an adaptive controller, the controller integration advantages of the principle of minimum is not affected by the control system of linear or nonlinear constraints, and the end state and free time, is accused of quantity can be controlled and are free to wait for a characteristic, using the minimum controller application example and simulation, the results show that the minimum principle of the designed controller has the ideal control effect.

Optimal Control Theory

2018 ◽  
Author(s):  
John E. Prussing
Keyword(s):  
Optimal Control ◽  
Control Theory ◽  
Optimal Control Theory ◽  
Necessary Conditions ◽  
Minimum Principle ◽  
Minimum Cost ◽  
Initial Time ◽  
Pontryagin Minimum Principle ◽  
Final Time ◽  
Terminal Constraints

Optimal Control Theory is reviewed in detail. We consider a dynamic system that operates between a specified initial time and a final time which may be specified or unspecified. Necessary conditions for a minimum cost functional are derived. Terminal constraints are considered. Pontryagin Minimum Principle is discussed.

Improved energy management strategy for a hybrid fuel cell/battery system

2017 ◽  
Vol 36 (4) ◽  
pp. 1008-1027 ◽  
Author(s):  
Bachir Bendjedia ◽  
Nassim Rizoug ◽  
Moussa Boukhnifer ◽  
Farid Bouchafaa
Keyword(s):  
Fuel Cell ◽  
Energy Management ◽  
Management Strategies ◽  
Experimental Results ◽  
Frequency Separation ◽  
Energy Management Strategy ◽  
Real Time System ◽  
Content Type ◽  
Depth Of Discharge ◽  
Battery State Of Charge

Purpose The purpose of this paper is to propose and compare two energy management strategies (EMSs). First, a classic method based on frequency separation with fixed limits on fuel cell (FC) power is presented and tested. Then, the improvement of the classic strategy is developed and implemented when the main enhancements are its ease of implementation, hydrogen economy and extending hybrid source lifetime. Design/methodology/approach The proposed EMS is developed using an online variable power limitation of the FC depending on the battery state of charge while ensuring that the energy of batteries remains in its operating depth of discharge (DOD) range. Findings In the objective to show the benefits of the developed strategy, a comparative analysis was conducted between two strategies. The simulation and experimental results show the effectiveness and gains obtained by the improved energy management system (IEMS) in terms of fuel economy (13 per cent) and decreasing the applied stress on the FC (22 per cent) which leads to a longer life span of the whole system. Originality/value The proposed approach is developed and tested by simulation. To confirm it, a test bench has been assembled as hardware in the loop (HIL) real-time system. The presented experimental results confirm the efficiency and show the providing gains of the IEMS.

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