8 research outputs found

    Cost-optimal energy management of hybrid electric vehicles using fuel cell/battery health-aware predictive control

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    Energy management is an enabling technology for increasing the economy of fuel cell/battery hybrid electric vehicles. Existing efforts mostly focus on optimization of a certain control objective (e.g., hydrogen consumption), without sufficiently considering the implications for on-board power sources degradation. To address this deficiency, this article proposes a cost-optimal, predictive energy management strategy, with an explicit consciousness of degradation of both fuel cell and battery systems. Specifically, we contribute two main points to the relevant literature, with the purpose of distinguishing our study from existing ones. First, a model predictive control framework, for the first time, is established to minimize the total running cost of a fuel cell/battery hybrid electric bus, inclusive of hydrogen cost and costs caused by fuel cell and battery degradation. The efficacy of this framework is evaluated, accounting for various sizes of prediction horizon and prediction uncertainties. Second, the effects of driving and pricing scenarios on the optimized vehicular economy are explored

    Preliminary design of a fuel cell/battery hybrid powertrain for a heavy-duty yard truck for port logistics

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    Abstract The maritime transport and the port-logistic industry are key drivers of economic growth, although, they represent major contributors to climate change. In particular, maritime port facilities are typically located near cities or residential areas, thus having a significant direct environmental impact, in terms of air and water quality, as well as noise. The majority of the pollutant emissions in ports comes from cargo ships, and from all the related ports activities carried out by road vehicles. Therefore, a progressive reduction of the use of fossil fuels as a primary energy source for these vehicles and the promotion of cleaner powertrain alternatives is in order. The present study deals with the design of a new propulsion system for a heavy-duty vehicle for port applications. Specifically, this work aims at laying the foundations for the development of a benchmark industrial cargo–handling hydrogen-fueled vehicle to be used in real port operations. To this purpose, an on-field measurement campaign has been conducted to analyze the duty cycle of a commercial Diesel-engine yard truck currently used for terminal ports operations. The vehicle dynamics has been numerically modeled and validated against the acquired data, and the energy and power requirements for a plug-in fuel cell/battery hybrid powertrain replacing the Diesel powertrain on the same vehicle have been evaluated. Finally, a preliminary design of the new powertrain and a rule-based energy management strategy have been proposed, and the electric energy and hydrogen consumptions required to achieve the target driving range for roll-on and roll-off operations have been estimated. The results are promising, showing that the hybrid electric vehicle is capable of achieving excellent energy performances, by means of an efficient use of the fuel cell. An overall amount of roughly 12 kg of hydrogen is estimated to be required to accomplish the most demanding port operation, and meet the target of 6 h of continuous operation. Also, the vehicle powertrain ensures an adequate all-electric range, which is between approximately 1 and 2 h depending on the specific port operation. Potentially, the hydrogen-fueled yard truck is expected to lead to several benefits, such as local zero emissions, powertrain noise elimination, reduction of the vehicle maintenance costs, improving of the energy management, and increasing of operational efficiency

    Comparison of decentralized ADMM optimization algorithms for power allocation in modular fuel cell vehicles

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    The advanced modular powertrains are envisioned as primary part of future hybrid fuel cell vehicles (FCVs). The existing papers in the literature solely cope with the hardware side of modularity, while the software side is also vital to capitalize on the total capacity of these powertrains. Driven by this motivation, this article puts forward a comparative study of two novel decentralized convex optimization frameworks based on alternating direction method of multipliers (ADMM) to solve a multi-objective power allocation strategy (PAS) problem in a modular FCV (MFCV). The MFCV in this article is composed of two fuel cell (FC) stacks and a battery pack. Despite the existing centralized strategies for such a modular system, this manuscript proposes two decentralized PASs (Dec-PASs) based on Consensus ADMM (C-ADMM) and Proximal Jacobian ADMM (PJ-ADMM) to bridge the gap regarding the appreciation of modularity in software terms. Herein, after formulating the central PAS optimization problem, the principle of utilizing such decentralized algorithms is presented in detail. Subsequently, the performance of the proposed Dec-PASs is examined through several numerical simulations as well as experiments on a developed small-scale test bench. The obtained results illustrate that decomposition into decentralized forms enables solving the complex PAS optimization problem faster and provides modularity and flexibility. Furthermore, the proposed Dec-PASs can cope with fault and malfunction and thus augment the durability and robustness of modular powertrain systems

    An online self cold startup methodology for PEM fuel cells in vehicular applications

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    This paper puts forward an adaptive cold start strategy for a proton exchange membrane fuel cell (PEMFC) based on maximum power mode. The proposed strategy consists of a water evacuation process after PEMFC shutdown and a self-heating process at PEMFC cold startup. To maximize the performance of the suggested strategy, an optimal operating condition for the cold start procedure is sought first. In this respect, an experimental parametric study is performed to explore the impact of fan velocity, micro-short circuit, anode pressure, and purge procedure on the PEMFC cold start performance. After laying down the proper conditions, the proposed cold start procedure is implemented on a test bench for experimental validations. The self-heating process is based on an online adaptive algorithm that maximizes the PEMFC's internal heat depending on its operating parameters' variation. In fact, this algorithm attempts to keep the current density at high levels, leading to PEMFC's performance improvement achieved by membrane hydration and temperature increase. The experimental results confirm the effectiveness of the proposed strategy, which presents a fast and cost-effective PEMFC's cold start. © 2020 IEEE

    Energy management strategies for fuel cell vehicles: A comprehensive review of the latest progress in modeling, strategies, and future prospects

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    Fuel cell vehicles (FCVs) are considered a promising solution for reducing emissions caused by the transportation sector. An energy management strategy (EMS) is undeniably essential in increasing hydrogen economy, component lifetime, and driving range. While the existing EMSs provide a range of performance levels, they suffer from significant shortcomings in robustness, durability, and adaptability, which prohibit the FCV from reaching its full potential in the vehicle industry. After introducing the fundamental EMS problem, this review article provides a detailed description of the FCV powertrain system modeling, including typical modeling, degradation modeling, and thermal modeling, for designing an EMS. Subsequently, an in-depth analysis of various EMS evolutions, including rule-based and optimization-based, is carried out, along with a thorough review of the recent advances. Unlike similar studies, this paper mainly highlights the significance of the latest contributions, such as advanced control theories, optimization algorithms, artificial intelligence (AI), and multi-stack fuel cell systems (MFCSs). Afterward, the verification methods of EMSs are classified and summarized. Ultimately, this work illuminates future research directions and prospects from multi-disciplinary standpoints for the first time. The overarching goal of this work is to stimulate more innovative thoughts and solutions for improving the operational performance, efficiency, and safety of FCV powertrains

    A comprehensive study of key Electric Vehicle (EV) components, technologies, challenges, impacts, and future direction of development

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    Abstract: Electric vehicles (EV), including Battery Electric Vehicle (BEV), Hybrid Electric Vehicle (HEV), Plug-in Hybrid Electric Vehicle (PHEV), Fuel Cell Electric Vehicle (FCEV), are becoming more commonplace in the transportation sector in recent times. As the present trend suggests, this mode of transport is likely to replace internal combustion engine (ICE) vehicles in the near future. Each of the main EV components has a number of technologies that are currently in use or can become prominent in the future. EVs can cause significant impacts on the environment, power system, and other related sectors. The present power system could face huge instabilities with enough EV penetration, but with proper management and coordination, EVs can be turned into a major contributor to the successful implementation of the smart grid concept. There are possibilities of immense environmental benefits as well, as the EVs can extensively reduce the greenhouse gas emissions produced by the transportation sector. However, there are some major obstacles for EVs to overcome before totally replacing ICE vehicles. This paper is focused on reviewing all the useful data available on EV configurations, battery energy sources, electrical machines, charging techniques, optimization techniques, impacts, trends, and possible directions of future developments. Its objective is to provide an overall picture of the current EV technology and ways of future development to assist in future researches in this sector

    Design and control of the energy management system of a smart vehicle

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    This thesis demonstrates the design of two high efficiency controllers, one non-predictive and the other predictive, that can be used in both parallel and power-split connected plug-in hybrid electric vehicles. Simulation models of three different commercially available vehicles are developed from measured data for necessary testing and comparisons of developed controllers. Results prove that developed controllers perform better than the existing controllers in terms of efficiency, fuel consumption, and emissions

    Energy storage for frequency regulation on the electric grid

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    Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2012.Cataloged from PDF version of thesis.Includes bibliographical references (p. 271-280).Ancillary services such as frequency regulation are required for reliable operation of the electric grid. Currently, the same traditional thermal generators that supply bulk power also perform nearly all frequency regulation. Instead, using high power energy storage resources to provide frequency regulation can allow traditional thermal generators to operate more smoothly. However, using energy storage alone for frequency regulation would require an unreasonably large energy storage capacity. Duration curves for energy capacity and instantaneous ramp rate are used to evaluate the requirements and benefits of using energy storage for a component of frequency regulation. Filtering is used to separate the portion of a frequency regulation control signal suitable for provision by an energy storage unit from the portion suitable for provision by traditional thermal generating resources. Not all frequency regulation signals are equally amenable to the filtering approach used here. Data from two U.S. control areas are used to demonstrate the techniques and the results are compared.by Olivia Leitermann.Ph.D
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