Contribution Of Developing A Prognostics Based Energy Management Strategy For Fuel Cell Hybrid System Application To A Fuel Cell Battery Hybrid Electric Vehicle

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Contribution of Developing a Prognostics-based Energy Management Strategy for Fuel Cell Hybrid System - Application to a Fuel Cell/battery Hybrid Electric Vehicle

Author : Meiling Yue
Publisher :
ISBN 13 :
Total Pages : 169 pages
Book Rating : 4.:/5 (115 download)

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Book Synopsis Contribution of Developing a Prognostics-based Energy Management Strategy for Fuel Cell Hybrid System - Application to a Fuel Cell/battery Hybrid Electric Vehicle by : Meiling Yue

Download or read book Contribution of Developing a Prognostics-based Energy Management Strategy for Fuel Cell Hybrid System - Application to a Fuel Cell/battery Hybrid Electric Vehicle written by Meiling Yue and published by . This book was released on 2019 with total page 169 pages. Available in PDF, EPUB and Kindle. Book excerpt: Fuel cell hybrid propulsion system is gaining momentum in today's automotive market and offers a sustainable solution for the world climate change in the transport sector. However, the durability and reliability of the power sources used in the hybrid system are the inevitable obstacles for its massive commercialization. To optimize and maximize the lifespan of the hybrid system, a prognostics and health management (PHM) approach is deployed to manage and mitigate the power source degradation behaviour and applied to a fuel cell hybrid electric vehicle.In this context, two main contributions are made. The first stage is to deploy a prognostics method that can be used in the hybrid system. Particle filtering, as a commonly used state estimation method, is adapted for prognostics purpose in this thesis. It is used to handle the imprecise and uncertain degradation data and estimate the remaining useful life. The method is validated by historical fuel cell and battery datasets and the results are evaluated by the designed prognostics metrics.Subsequently, a second stage on the health management aspect of PHM is proposed. As the split of demanded power in a hybrid system is managed by an energy management strategy (EMS), the orientation of this stage is to develop a health-conscious EMS in the context of PHM. A great quantity of researches on prognostics with finished experimental data have been found in the literature, while how to use the prognostics results to make corrective control actions is rarely discussed. To help against this vacancy in hybrid system applications, a prognostics-enabled decision-making process is designed. The performance is evaluated by quantifying the degradation and the lifetime of the system in a simulated environment and a discussion on prognostics occurrence is launched for further investigations on maintenance.

Deep Reinforcement Learning-based Energy Management for Hybrid Electric Vehicles

Author : Li Yeuching
Publisher : Springer Nature
ISBN 13 : 3031792068
Total Pages : 123 pages
Book Rating : 4.0/5 (317 download)

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Book Synopsis Deep Reinforcement Learning-based Energy Management for Hybrid Electric Vehicles by : Li Yeuching

Download or read book Deep Reinforcement Learning-based Energy Management for Hybrid Electric Vehicles written by Li Yeuching and published by Springer Nature. This book was released on 2022-06-01 with total page 123 pages. Available in PDF, EPUB and Kindle. Book excerpt: The urgent need for vehicle electrification and improvement in fuel efficiency has gained increasing attention worldwide. Regarding this concern, the solution of hybrid vehicle systems has proven its value from academic research and industry applications, where energy management plays a key role in taking full advantage of hybrid electric vehicles (HEVs). There are many well-established energy management approaches, ranging from rules-based strategies to optimization-based methods, that can provide diverse options to achieve higher fuel economy performance. However, the research scope for energy management is still expanding with the development of intelligent transportation systems and the improvement in onboard sensing and computing resources. Owing to the boom in machine learning, especially deep learning and deep reinforcement learning (DRL), research on learning-based energy management strategies (EMSs) is gradually gaining more momentum. They have shown great promise in not only being capable of dealing with big data, but also in generalizing previously learned rules to new scenarios without complex manually tunning. Focusing on learning-based energy management with DRL as the core, this book begins with an introduction to the background of DRL in HEV energy management. The strengths and limitations of typical DRL-based EMSs are identified according to the types of state space and action space in energy management. Accordingly, value-based, policy gradient-based, and hybrid action space-oriented energy management methods via DRL are discussed, respectively. Finally, a general online integration scheme for DRL-based EMS is described to bridge the gap between strategy learning in the simulator and strategy deployment on the vehicle controller.

Predictive Energy Management for Fuel Cell Hybrid Electric Vehicle

Author : Yang Zhou
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (122 download)

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Book Synopsis Predictive Energy Management for Fuel Cell Hybrid Electric Vehicle by : Yang Zhou

Download or read book Predictive Energy Management for Fuel Cell Hybrid Electric Vehicle written by Yang Zhou and published by . This book was released on 2020 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Fuel cell electric vehicles have been widely deemed as the promising substitution against traditional internal combustion engine-based vehicles. To reduce the vehicular operating costs, a practical solution at current stage is to efficiently and healthily use the hybrid propulsion systems. Such task can be fulfilled via reliable energy management strategies, which coordinate the outputs of multiple energy sources to satisfy the vehicular power request.In such context, this PhD thesis intends to devise intelligent energy management strategies for fuel cell hybrid electric vehicles. Compared to existing control strategies, this thesis especially focuses on the possibility of combining the forecasted driving information with the real-time optimal control framework. Several driving prediction techniques are developed to estimate the upcoming driving conditions, like the vehicle's speed, battery state-of-charge reference and driving pattern information. Thereafter, model predictive control is selected for real-time decision-making, since it is capable of handling the time-varying constrained systems and is convenient for the integration of driving predictive information. Based on the forecasted results and model predictive control, several predictive energy management strategies are established, aiming at saving hydrogen consumption and enhancing fuel cell durability versus benchmark strategies.Both offline simulation and software-in-the-loop testing have verified the functionality and real-time suitability of the proposed strategies.

Health Conscious Energy Management Strategies for Fuel Cell/battery Hybrid Vehicles

Author : Yongqiang Wang
Publisher :
ISBN 13 :
Total Pages : 162 pages
Book Rating : 4.5/5 (825 download)

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Book Synopsis Health Conscious Energy Management Strategies for Fuel Cell/battery Hybrid Vehicles by : Yongqiang Wang

Download or read book Health Conscious Energy Management Strategies for Fuel Cell/battery Hybrid Vehicles written by Yongqiang Wang and published by . This book was released on 2021 with total page 162 pages. Available in PDF, EPUB and Kindle. Book excerpt: There have been many efforts to combat climate change to provide a sustainable future. Fuel cell vehicles can reduce emissions for the transportation sector as their only by-product is water. One major barrier towards commercialization is the cost of fuel cell stacks. Extending the operating life of fuel cells can lower their overall cost. Thus it is important to study the effects of degradation when designing fuel cell/battery hybrid vehicles. We have collected test data from the University of Delaware's latest fuel cell bus by implementing two-way on-board communication systems. A vehicle model was built in MATLAB based on the collected data. Various options including health conscious energy management strategies(offline and real-time) and system sizing were explored in this study to reduce the degradation of fuel cell stacks and batteries to improve their lifetime.

Hybridization, Diagnostic and Prognostic of PEM Fuel Cells

Author : Samir Jemei
Publisher : John Wiley & Sons
ISBN 13 : 1119563437
Total Pages : 242 pages
Book Rating : 4.1/5 (195 download)

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Book Synopsis Hybridization, Diagnostic and Prognostic of PEM Fuel Cells by : Samir Jemei

Download or read book Hybridization, Diagnostic and Prognostic of PEM Fuel Cells written by Samir Jemei and published by John Wiley & Sons. This book was released on 2018-10-25 with total page 242 pages. Available in PDF, EPUB and Kindle. Book excerpt: Hydrogen is the most abundant element in the universe. It has a place in the energy mix of the future, especially regarding fuel cells (FCs). This book is an investigation into FCs. Prominence is given to the subject of PEMFCs (proton exchange membrane fuel cells) as they offer interesting perspectives on transport and stationary applications. This being said, a number of technological and scientific obstacles remain to be overcome before an industrial level of development can be reached.

Development of a Fuel Cell Plug-in Hybrid Electric Vehicle and Vehicle Simulator for Energy Management Assessment

Author : Andrew Lee Meintz
Publisher :
ISBN 13 :
Total Pages : 316 pages
Book Rating : 4.:/5 (861 download)

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Book Synopsis Development of a Fuel Cell Plug-in Hybrid Electric Vehicle and Vehicle Simulator for Energy Management Assessment by : Andrew Lee Meintz

Download or read book Development of a Fuel Cell Plug-in Hybrid Electric Vehicle and Vehicle Simulator for Energy Management Assessment written by Andrew Lee Meintz and published by . This book was released on 2011 with total page 316 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This dissertation offers a description of the development of a fuel cell plug-in hybrid electric vehicle focusing on the propulsion architecture selection, propulsion system control, and high-level energy management. Two energy management techniques have been developed and implemented for real-time control of the vehicle. The first method is a heuristic method that relies on a short-term moving average of the vehicle power requirements. The second method utilizes an affine function of the short-term and long-term moving average vehicle power requirements. The development process of these methods has required the creation of a vehicle simulator capable of estimating the effect of changes to the energy management control techniques on the overall vehicle energy efficiency. Furthermore, the simulator has allowed for the refinement of the energy management methods and for the stability of the method to be analyzed prior to on-road testing. This simulator has been verified through on-road testing of a constructed prototype vehicle under both highway and city driving schedules for each energy management method. The results of the finalized vehicle control strategies are compared with the simulator predictions and an assessment of the effectiveness of both strategies is discussed. The methods have been evaluated for energy consumption in the form of both hydrogen fuel and stored electricity from grid charging"--Abstract, leaf iii.

Hybrid Electric Vehicles

Author : Simona Onori
Publisher : Springer
ISBN 13 : 1447167813
Total Pages : 121 pages
Book Rating : 4.4/5 (471 download)

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Book Synopsis Hybrid Electric Vehicles by : Simona Onori

Download or read book Hybrid Electric Vehicles written by Simona Onori and published by Springer. This book was released on 2015-12-16 with total page 121 pages. Available in PDF, EPUB and Kindle. Book excerpt: This SpringerBrief deals with the control and optimization problem in hybrid electric vehicles. Given that there are two (or more) energy sources (i.e., battery and fuel) in hybrid vehicles, it shows the reader how to implement an energy-management strategy that decides how much of the vehicle’s power is provided by each source instant by instant. Hybrid Electric Vehicles: •introduces methods for modeling energy flow in hybrid electric vehicles; •presents a standard mathematical formulation of the optimal control problem; •discusses different optimization and control strategies for energy management, integrating the most recent research results; and •carries out an overall comparison of the different control strategies presented. Chapter by chapter, a case study is thoroughly developed, providing illustrative numerical examples that show the basic principles applied to real-world situations. The brief is intended as a straightforward tool for learning quickly about state-of-the-art energy-management strategies. It is particularly well-suited to the needs of graduate students and engineers already familiar with the basics of hybrid vehicles but who wish to learn more about their control strategies.

Application of Artificial Intelligence in Hybrid Electric Vehicle Energy Management

Author : Jili Tao
Publisher : Elsevier
ISBN 13 : 0443131902
Total Pages : 348 pages
Book Rating : 4.4/5 (431 download)

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Book Synopsis Application of Artificial Intelligence in Hybrid Electric Vehicle Energy Management by : Jili Tao

Download or read book Application of Artificial Intelligence in Hybrid Electric Vehicle Energy Management written by Jili Tao and published by Elsevier. This book was released on 2024-06-07 with total page 348 pages. Available in PDF, EPUB and Kindle. Book excerpt: Application of Artificial Intelligence in Hybrid Electric Vehicle Energy Management presents the state-of-the-art in hybrid electric vehicle system modelling and management. With a focus on learning-based energy management strategies, the book provides detailed methods, mathematical models, and strategies designed to optimize the energy management of the energy supply module of a hybrid vehicle.The book first addresses the underlying problems in Hybrid Electric Vehicle (HEV) modeling, and then introduces several artificial intelligence-based energy management strategies of HEV systems, including those based on fuzzy control with driving pattern recognition, multi objective optimization, fuzzy Q-learning and Deep Deterministic Policy Gradient (DDPG) algorithms. To help readers apply these management strategies, the book also introduces State of Charge and State of Health prediction methods and real time driving pattern recognition. For each application, the detailed experimental process, program code, experimental results, and algorithm performance evaluation are provided.Application of Artificial Intelligence in Hybrid Electric Vehicle Energy Management is a valuable reference for anyone involved in the modelling and management of hybrid electric vehicles, and will be of interest to graduate students, researchers, and professionals working on HEVs in the fields of energy, electrical, and automotive engineering. Provides a guide to the modeling and simulation methods of hybrid electric vehicle energy systems, including fuel cell systems Describes the fundamental concepts and theory behind CNN, MPC, fuzzy control, multi objective optimization, fuzzy Q-learning and DDPG Explains how to use energy management methods such as parameter estimation, Q-learning, and pattern recognition, including battery State of Health and State of Charge prediction, and vehicle operating conditions

Energy Consumption Minimization Strategy for Fuel Cell Hybrid Electric Vehicles

Author : Huan Li
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (19 download)

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Book Synopsis Energy Consumption Minimization Strategy for Fuel Cell Hybrid Electric Vehicles by : Huan Li

Download or read book Energy Consumption Minimization Strategy for Fuel Cell Hybrid Electric Vehicles written by Huan Li and published by . This book was released on 2018 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Global warming, environment pollution and exhaustion of petroleum energies have risen their attention of the humanity over the world. Fuel cell hybrid electric vehicle (FCHEV) taking hydrogen as fuel and have zero emission, is thought by public and private organisms as one of the best ways to solve these problems. This PhD dissertation consider a FCHEV with three power sources: fuel cell, battery and supercapacitor, which increases the difficult to design an energy management strategy (EMS) to split the power between the different power sources.Among the EMS available in the current literature, the Equivalent consumption minimization strategy (ECMS) was selected because it allows a local optimization without rely on prior knowledge of driving condition while giving optimal results.Due to low energy density of supercapacitor, its equivalent hydrogen consumption is neglected in most bibliographic references, which not only counter to the aim of minimizing whole hydrogen consumption but also increase the complication of EMS due to the need of an additional EMS to calculate supercapacitor power demand. Thus, a sequential quadratic programming ECMS (SECMS) strategy is proposed to consider energy cost of all three power sources into the objective function. A rule based control strategy (RBCS) and hybrid strategy (HEOS) are also designed in order to to be compared with SECMS. Degradation of energy sources represents a major challenge for the stability of the developed SECMS system. So, based on online estimating state of heath of fuel cell and battery, an adaptive ECMS (AECMS) has been designed through adjusting the equivalent factor and dynamical change rate of fuel cell. The simulation results show that the AECMS can ensure the charge sustenance of battery and the increase of fuel cell durability.To validate the proposed energy management algorithms and the numerical models an exerimental test bench has been built around the real time interface DSPACE. The comparison of the simulation and experimental results showed that the proposed SECMS is operated at around maximum efficiency, supercapacitor supplies peak power, battery works as the energy buffer. It has been proved that the neglect of supercapacitor equivalent hydrogen consumption in ECMS leads to not optimal operation. Compared with RBCS and HEOS, SECMS has least hydrogen consumption and most stable fuel cell current.

Modeling, Simulation and Optimization of Fuel Cell/battery Hybrid Powertrains

Author : Piyush Bubna
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (727 download)

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Book Synopsis Modeling, Simulation and Optimization of Fuel Cell/battery Hybrid Powertrains by : Piyush Bubna

Download or read book Modeling, Simulation and Optimization of Fuel Cell/battery Hybrid Powertrains written by Piyush Bubna and published by . This book was released on 2010 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Fuel cells have emerged as one of the most promising candidates for fuel-efficient and emission-free vehicle power generation. Fuel cells are typically paired with reversible energy storage devices such as batteries or ultracapacitors to create hybrid electric powertrains. The electrification of the propulsion system and the presence of multiple onboard power sources require optimization of the hybrid system design in order to achieve good performance, high fuel economy, and enhanced component life at low cost. The overall goal of this research is to develop accurate vehicle models and conduct simulations to explore and demonstrate improvements in a fuel cell/battery hybrid bus. The first part of this thesis presents the features incorporated to improve a hybrid powertrain simulation package called Light, Fast and Modifiable (LFM). The improved LFM simulator was validated against test data acquired from various sensors onboard UD's Phase 1 fuel cell bus, and shown to be a reliable tool to simulate hybrid powertrain performance which could be used to perform design and optimization studies of future fuel cell hybrid systems. This attribute of LFM was then demonstrated by optimizing the fuel cell/battery hybrid power management by introducing a new prediction-based power management strategy. Simulation results for this strategy showed significant improvements in fuel cell system efficiency and reduction in hydrogen consumption compared to a conventional, baseline strategy of charge sustenance. A stable power request which promotes fuel cell durability was also realized with the help of this novel strategy. Finally, the benefits predicted from simulation studies were confirmed through implementation of the proposed strategy in the Phase 1 fuel cell/battery hybrid bus. It was concluded that the prediction-based strategy will lead to energy savings for transit applications. The validated LFM tool was next used to evaluate one approach to reducing battery stress by adding an ultracapacitor module, and thereby enhancing battery lifetime. Simulation of the energy storage performance showed a substantial reduction in battery current-load and energy throughput for the blended storage system, which are two of the contributing factors towards battery degradation. These results have opened up new research directions in which powertrain simulations can help in further evaluation of the blended storage concept and assess its feasibility and usefulness in electric-drive vehicles. Finally, the thermal behavior of the Altairnano LiTi battery, the future battery of UD fuel cell buses, was investigated. Preliminary experiments were conducted to understand the thermal behavior of batteries under typical operating conditions. A model was developed to predict the temperature during charging and discharging of the battery. The findings of this work should prove useful in designing effective and efficient battery thermal management systems.

Optimal Energy Management Strategy for a Fuel Cell Hybrid Electric Vehicle

Author : Thomas P. Fletcher
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (16 download)

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Book Synopsis Optimal Energy Management Strategy for a Fuel Cell Hybrid Electric Vehicle by : Thomas P. Fletcher

Download or read book Optimal Energy Management Strategy for a Fuel Cell Hybrid Electric Vehicle written by Thomas P. Fletcher and published by . This book was released on 2017 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Power Management Strategy of a Fuel Cell Hybrid Electric Vehicle with Integrated Ultra-capacitor with Driving Pattern Recognition

Author : Puneet Jethani
Publisher :
ISBN 13 :
Total Pages : 101 pages
Book Rating : 4.:/5 (131 download)

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Book Synopsis Power Management Strategy of a Fuel Cell Hybrid Electric Vehicle with Integrated Ultra-capacitor with Driving Pattern Recognition by : Puneet Jethani

Download or read book Power Management Strategy of a Fuel Cell Hybrid Electric Vehicle with Integrated Ultra-capacitor with Driving Pattern Recognition written by Puneet Jethani and published by . This book was released on 2017 with total page 101 pages. Available in PDF, EPUB and Kindle. Book excerpt: The greenhouse gases in the atmosphere have reached a highest level due to high number of vehicles. A Fuel Cell Hybrid Electric Vehicle (FCHEV) has zero greenhouse gas emissions compared to conventional ICE vehicles or Hybrid Electric Vehicles and hence is a better alternative. All Electric Vehicle (AEVs) have longer charging time which is unfavorable. A fully charged battery gives less range compared to a FCHEV with a full hydrogen tank. So FCHEV has an advantage of a quick fuel up and more mileage than AEVs. A Proton Electron Membrane Fuel Cell (PEMFC) is the commonly used kind of fuel cell vehicles but it possesses slow current dynamics and hence not suitable to be the sole power source in a vehicle. Therefore, improving the transient power capabilities of fuel cell to satisfy the road load demand is critical. This research studies integration of Ultra-Capacitor (UC) to FCHEV. The objective is to analyze the effect of integrating UCs on the transient response of FCHEV powertrain. UCs has higher power density which can overcome slow dynamics of fuel cell. A power management strategy utilizing peak power shaving strategy is implemented. The goal is to decrease power load on batteries and operate fuel cell stack in it’s most efficient region. Complete model to simulate the physical behavior of UC-Integrated FCHEV (UC-FCHEV) is developed using Matlab/SIMULINK. The fuel cell polarization curve is utilized to devise operating points of the fuel cell to maintain its operation at most efficient region. Results show reduction of hydrogen consumption in aggressive US06 drive cycle from 0.29 kg per drive cycle to 0.12 kg. The maximum charge/discharge battery current was reduced from 286 amperes to 110 amperes in US06 drive cycle. Results for the FUDS drive cycle show a reduction in fuel consumption from 0.18 kg to 0.05 kg in one drive cycle. This reduction in current increases the life of the battery since its protected from overcurrent. The SOC profile of the battery also shows that the battery is not discharged to its minimum threshold which increasing the health of the battery based on number of charge/discharge cycles.

Energy Management Control Strategies for Fuel Cell Hybrid Electric Vehicles

Author : Askin Minaz
Publisher :
ISBN 13 :
Total Pages : 166 pages
Book Rating : 4.:/5 (154 download)

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Book Synopsis Energy Management Control Strategies for Fuel Cell Hybrid Electric Vehicles by : Askin Minaz

Download or read book Energy Management Control Strategies for Fuel Cell Hybrid Electric Vehicles written by Askin Minaz and published by . This book was released on 2006 with total page 166 pages. Available in PDF, EPUB and Kindle. Book excerpt:

An Energy Management Strategy for Plug-in Hybrid Electric Vehicles

Author : Benjamin Bader
Publisher :
ISBN 13 :
Total Pages : 139 pages
Book Rating : 4.:/5 (112 download)

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Book Synopsis An Energy Management Strategy for Plug-in Hybrid Electric Vehicles by : Benjamin Bader

Download or read book An Energy Management Strategy for Plug-in Hybrid Electric Vehicles written by Benjamin Bader and published by . This book was released on 2014 with total page 139 pages. Available in PDF, EPUB and Kindle. Book excerpt: This dissertation formulates a proposal for a real time implementable energy management strategy (EMS) for plug-in hybrid electric vehicles. The EMS is developed to minimize vehicle fuel consumption through the utilisation of stored electric energy and high-efficiency operation of powertrain components. This objective is achieved through the development of a predictive EMS, which, in addition to fuel efficiency, is optimized in terms of computational cost and drivability. The requirement for an EMS in hybrid powertrain vehicles stems from the integration of two energy stores and converters in the powertrain; in the case of hybrid electric vehicles (HEVs) usually a combustion engine and one or more electric machines powered by a battery. During operation of the vehicle the EMS controls power distribution between engine and electric traction motor. Power distribution is optimized according to the operating point dependent efficiencies of the components, energy level of the battery and trip foreknowledge. Drivability considerations, e.g. frequency of engine starts, can also be considered. Due to high oil prices and legislative requirements caused by the environmental impact of greenhouse emissions, fuel economy has gained importance in recent years. In addition to increased fuel economy, powertrain hybridization permits the substituton of fuel for electrical energy by implementing an external recharging option for the battery. This vehicle class, incorporating a battery rechargeable via the electrical grid, is known as a plug-in HEV (PHEV). PHEV share characteristics of both HEVs and all-electric vehicles combining several advantages of both technologies. The rechargeable battery feature of the PHEVs makes their EMS development espe-cially challenging. For minimal fuel consumption, the battery is discharged optimally over the whole trip length, prioritising electrical energy when driving conditions are such that its use maximises the fuel saving that can be achieved. Therefore, an EMS for a PHEV depends heavily on the availability of a priori knowledge about the trip, i.e. the knowledge about future vehicle speed and road grade. This requires the driver to indi-cate the route before trip start. The route knowledge in combination with GPS or Galileo based next generation navigation systems using information from a geographic in-formation system (GIS) about terrain height profile, road type (e.g. motorway or country road), and legal speed limits can be evaluated by a speed prediction algorithm including information about the driver's behaviour for a detailed prediction of the trip. These navigation systems and algorithms in combination with expected future advances and the deployment of technologies such as intelligent transport systems (ITS) and vehicle-to-vehicle communication (V2V), will make more exact traffic information available to further improve prediction. Despite expected advances in prediction quality, inaccuracy of prediction data has to be considered and is therefore regarded in this work. The EMS proposed in this dissertation combines different approaches which are exe-cuted step by step. A first approximation of the energy distribution during the trip is based on a mixed integer linear program (MILP), which gives the optimal energy state of the battery during the trip. This is especially important for trips with long uphill, downhill or urban phases, i.e. sections with a particularly high or lower power requirement. The results from MILP are then used by a dynamic programming (DP) algorithm to calculate optimal torque and gear using a receding prediction horizon. Using a receding prediction horizon, an important reduction of computational cost is achieved. Lastly, from the DP results a rule-based strategy is extracted using a support vector machine (SVM). This last step is necessary to ensure the drivability of the vehicle also for inaccurate prediction data.

Optimization of the Sizing and the Energy Management for a Hybrid Fuel Cell Vehicle Including Fuel Cell Dynamics and Durability Constraints

Download Optimization of the Sizing and the Energy Management for a Hybrid Fuel Cell Vehicle Including Fuel Cell Dynamics and Durability Constraints PDF Online Free

Author : Ramon Fonseca (Naiff da)
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (139 download)

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Book Synopsis Optimization of the Sizing and the Energy Management for a Hybrid Fuel Cell Vehicle Including Fuel Cell Dynamics and Durability Constraints by : Ramon Fonseca (Naiff da)

Download or read book Optimization of the Sizing and the Energy Management for a Hybrid Fuel Cell Vehicle Including Fuel Cell Dynamics and Durability Constraints written by Ramon Fonseca (Naiff da) and published by . This book was released on 2014 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The hydrogen, through the use of fuel cell stacks (FC), has been increasily considered as an energy possible option for the transport sector. Nevertheless, the technology related to its implementation in fuel cell vehicles has not reached the required maturity level. Therefore, this work intends to deal some of these existing limitations. More precisely, three topics represent the objectives of this work: The optimal sizing of the element present in the fuel cell hybrid vehicle. The development of an optimal energy management strategy oriented for real time applications and including the dynamic constraints of the FC system. The inclusion of the fuel cell durability in the vehicle energy management strategy. The first topic is tackled by the development of a sizing methodology adapted to the fuel cell hybrid vehicle application. Using a systematic approach, the proposed sizing method combine the performance requirements present in the vehicle's technical specifications, optimization algorithms, population mobility behavior and the economic viability of the design. The second assigned objective was developed using an optimization approach for the power split between the battery and the FC system. Through the adoption of a global optimization method allied with a predictive control strategy and the inclusion of the FC system dynamics, it was created an energy management algorithm oriented for real time applications. Finally, the fuel cell durability was included in this work by the integration of its degradation dynamics in the optimization problem, which is related to the vehicle's energy management. Such dynamic represents a constraint that should be taken into account in the power sharing between the FC system and battery.

Development and Evaluation of Intelligent Energy Management Strategies for Plug-in Hybrid Electric Vehicles

Author : Guoyuan Wu
Publisher :
ISBN 13 :
Total Pages : 28 pages
Book Rating : 4.:/5 (112 download)

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Book Synopsis Development and Evaluation of Intelligent Energy Management Strategies for Plug-in Hybrid Electric Vehicles by : Guoyuan Wu

Download or read book Development and Evaluation of Intelligent Energy Management Strategies for Plug-in Hybrid Electric Vehicles written by Guoyuan Wu and published by . This book was released on 2012 with total page 28 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this study, we proposed an intelligent energy management strategy for plug-in hybrid electric vehicles. At the trip level, the strategy takes into account a priori knowledge of vehicle location, roadway characteristics, and real-time traffic information on the travel route from intelligent transportation system technologies in generating synthesized velocity trajectory for the trip. The synthesized velocity trajectory is then used to determine charge-depleting control that is formulated as a mixed integer linear programming to minimize the total fuel consumption for the trip. The strategy can be extended to optimize fuel consumption at the tour level if a pre-planned travel itinerary for the tour and the information about available battery recharging opportunities at intermediate stops in the tour are available. The effectiveness of the proposed strategy, both for the trip-based and tour-based controls, was evaluated against the existing binary mode energy management strategy using a real-world example trip/tour in Southern California. The evaluation results show that the fuel savings of the proposed strategy over the binary mode strategy are around 10-15%.

Contribution to Prognostics of Proton Exchange Membrane Fuel Cells

Author : Dacheng Zhang
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (14 download)

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Book Synopsis Contribution to Prognostics of Proton Exchange Membrane Fuel Cells by : Dacheng Zhang

Download or read book Contribution to Prognostics of Proton Exchange Membrane Fuel Cells written by Dacheng Zhang and published by . This book was released on 2018 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the context of the energy transition, fuel cell becomes one of the promising alternative energy sources. Recently the spotlight is on fuel cell systems research, and more particularly on Proton Exchange Membrane Fuel Cell (PEMFCs) which is one of the best candidates for both stationary and transportation applications. Even if this technology is close to being competitive, it is not yet ready to be considered for a large scale industrial deployment because of its limited durability and reliability. Prognostics and Health Management (PHM) is a recent approach to manage and possibly extend life duration of technological systems. Prognostic techniques can provide an estimation of fuel cell State Of Health (SOH) and a prediction for their Remaining Useful Life (RUL) to help the manufacturers improving fuel cell performance and managing its lifespan.The objective of this work is to develop prognostic methodologies for the RUL prognosis adapted to the complexity of PEMFCs. Indeed, the PEMFC is a multi-scale and multi-physics system, and various challenges are faced:1. The definition of SOH to build a degradation indicator.2. The coexistence of both reversible and irreversible degradation phenomena.3. Taking into account different deterioration causes and effects of operating conditions.In the first part of our work, we conduct a state of the art analysis on PHM for PEMFCs, with the aim of proposing a SOH definition and building a degradation indicator for PEMFC prognosis purposes. And since PEMFC measurements are scarce, the state of the art on Lithium batteries, other electrochemical cells, is also explored.In the second part, we develop a particle filtering based prognostic algorithm for PEMFC, based on output power measurements. The first results show that the prognosis algorithm is disturbed by the existing reversible degradation. However, the irreversible degradation can be estimated thanks to characterization tests, such as Electrochemical Impedance Spectroscopy (EIS), which is applied from time to time. We propose thus an adapted & extended prognostic algorithm to take into account both health indicators: the output power degradation and the SOH degradation estimated from EIS characterization. The performance of the proposed algorithm is evaluated by different prognostic performance metrics, and the results show the interest of this approach.In the third part, the problem is addressed from a more theoretical point of view. Indeed, a system's degradation behavior is often correlated with internal and external covariates which are usually difficult to access owing to expensive measurement cost. Therefore, we first developed a prognostic approach with online inspections on the degradation covariate at a different level, and then we propose an approach for RUL prognosis based on an ensemble of models using different sources at different levels. The RUL predictions of both models are dynamically aggregated on the basis of prognostic performance evaluated on a set of historical data. Consequently, the prediction accuracy is improved by overcoming both models' drawbacks and leveraging their strengths. In the last part, we extend the problem to multi-level prognostics and explore new possibilities, which open new aspects for future research on PEMFC lifetime prognosis and management.