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Technical Paper

Fuel Cell Hybrid Electric Vehicle: Validated Fuel Cell and Battery Pack Model to Enhance Reliability in Performance Predictions

2024-04-09
2024-01-2188
In the face of the pressing climate crisis, a pivotal shift towards sustainability is imperative, particularly in the transportation sector, which contributed to nearly 22% of global Greenhouse Gas emissions in 2021. In this context, diversifying energy sources becomes paramount to prevent the collapse of sustainable infrastructure and harness the advantages of various technologies, such as Fuel Cell (FC) Hybrid Electric Vehicles. These vehicles feature powertrains comprising hydrogen FC stacks and battery packs, offering extended mileage, swift refueling times, and rapid dynamic responses. However, realizing these benefits hinges upon the adoption of a rigorously validated simulation platform capable of accurately forecasting vehicle performance across diverse design configurations and efficient Energy Management Strategies. Our study introduces a comprehensive microcar hybrid prototype model, encompassing all subsystems and auxiliaries.
Technical Paper

Fuel Cell Hybrid Electric Vehicle: An Integrated Approach for Sub-Optimal Controller in Real-Time Application

2024-04-09
2024-01-2187
Hydrogen technologies are among the main candidates to reduce carbon emissions in the automotive transport sector. Among the innovative solutions, Electric Vehicles (EVs) featuring hybrid powertrains, combining battery packs and hydrogen Fuel Cell (FC) stacks, are gaining prominence in our pursuit of sustainability objectives. Nonetheless, realizing the full potential of these hybrid vehicles hinges on the implementation of efficient Energy Management Strategies (EMS). In this study, we present an integrated EMS approach to achieve extended driving ranges and reduced energy consumption. This is achieved primarily by operating the FC within its high-efficiency range, while ensuring that the battery packs operate in a charge-sustaining mode. The EMS is crafted through an adaptive algorithm that takes into account various driving conditions to establish the most suitable sub-optimal control strategy.
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