Fuel-Cell and Battery Hybrid Source Optimal Power Management for Electric Mobility

Amamou, Ali; Ziadia, Marwa; Kélouwani, Sousso; Agbossou, Kodjo; Dubé, Yves

doi:10.1109/vppc.2018.8605030

Cited by 2 publications

(2 citation statements)

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“…They compared their simulation results with those of vehicle simulation software over HW and federal urban driving cycle (FUDS) driving cycles. Other researchers extended their optimizations beyond the EMS by finding the best power sources combination for optimal energy saving, using rule based methods, fuzzy logic control, genetic algorithm, particle swarm algorithms, and two‐dimensional pontryagin's minimum principle . Others used different versions of dynamic programming to achieve the optimal sizes while reducing operational costs .…”

Section: Introductionmentioning

confidence: 99%

Power sources sizing for a fuel cell hybrid vehicle

2020

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Fuel cell hybrid vehicles (FCHV) are attractive alternatives to fossil fuel based ones in terms of lowering levels of polluting emissions. This paper presents a methodology for modeling, sizing, and power management of FCHV. The aim of the study is to achieve the lowest cost of driving over different driving cycles taking into consideration the vehicle specifications and minimum drivability constraints. The tunnel dynamic programming (TDP) is used to find the optimal power split between the battery and the fuel cell to meet the power demand for driving. On the other hand, since cost is a major barrier hindering the commercialization of FCHV, Pareto front is used to determine the best combination of sizes to achieve the lowest operational cost. The analysis covers different driving cycles including a combination of the highway and urban driving cycles mimicking a realistic one. The focus on lithium titanate battery and the combination of TDP‐Pareto front are the significant contributions of this paper. Comparative results against a commercial hybrid vehicle showed that the proposed model found a more efficient design in terms of hydrogen consumption and more capable in meeting aggressive drivability constraints as the electric motor size selected is greater.

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Section: Introductionmentioning

confidence: 99%

Power sources sizing for a fuel cell hybrid vehicle

2020

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“…In an FCEV, an EMS configures the hybrid-power sources to provide sufficient energy for driving the vehicle in different traffic conditions while offering a timely response to address possible fast power changes due to accelerating or braking by dynamically balancing load sharing among power sources [12][13][14].…”

Section: Introductionmentioning

confidence: 99%

Traffic-Condition-Prediction-Based HMA-FIS Energy-Management Strategy for Fuel-Cell Electric Vehicles

Yao

et al. 2019

Energies

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In the field of Fuel Cell Electric Vehicles (FCEVs), a fuel-cell stack usually works together with a battery to improve powertrain performance. In this hybrid-power system, an Energy Management Strategy (EMS) is essential to configure the hybrid-power sources to provide sufficient energy for driving the FCEV in different traffic conditions. The EMS determines the overall performance of the power supply system; accordingly, EMS research has important theoretical significance and application values on the improvement of energy-utilization efficiency and the serviceability of vehicles' hybrid-power sources. To overcome the deficiency of apparent filtering lag and improve the adaptability of an EMS to different traffic conditions, this paper proposes a novel EMS based on traffic-condition predictions, frequency decoupling and a Fuzzy Inference System (FIS). An Artificial Neural Network (ANN) was designed to predict traffic conditions according to the vehicle's running parameters; then, a Hull Moving Average (HMA) algorithm, with filter-window width decided by the prediction result, is introduced to split the demanded power and keep low-frequency components in order to meet the load characteristics of the fuel cell; afterward, an FIS was applied to manage power flows of the FCEV's hybrid-power sources and maintain the State of Change (SoC) of the battery in a predefined range. Finally, an FCEV simulation platform was built with MATLAB/Simulink and comparison simulations were carried out with the standard test cycle of the Worldwide harmonized Light vehicle Test Procedures (WLTPs). Simulation results showed that the proposed EMS could efficiently coordinate the hybrid-power sources and support the FCEV in following the reference speed with negligible control errors and sufficient power supply; the SoC of the battery was also maintained with good adaptability in different driving conditions.

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Fuel-Cell and Battery Hybrid Source Optimal Power Management for Electric Mobility

Cited by 2 publications

References 20 publications

Power sources sizing for a fuel cell hybrid vehicle

Power sources sizing for a fuel cell hybrid vehicle

Traffic-Condition-Prediction-Based HMA-FIS Energy-Management Strategy for Fuel-Cell Electric Vehicles

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