AAC 2019 Paper Abstract

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Paper TuBT1.3

Aliberti, Marco (University of Salerno), Arsie, Ivan (University of Salerno), Cricchio, Andrea (University of Salerno), PIANESE, CESARE (UNIVERSITY OF SALERNO), Polverino, Pierpaolo (University of Salerno), Sorrentino, Marco (University of Salerno)

A Model-Based Scenario Analysis for Assessing the Benefits of Fuel Cell Vehicle Hybridization

Scheduled for presentation during the Regular Session "Control & Estimation III : Energy sources" (TuBT1), Tuesday, June 25, 2019, 15:25−15:45, Chambord

9th IFAC International Symposium on Advances in Automotive Control, June 23-27, 2019, Orléans, France

This information is tentative and subject to change. Compiled on April 26, 2024

Keywords XEV (HEV,EV,FCEV,etc.)/Solar-Powered Vehicles, Fuel-cells, Hydrocarbon Fuel Reforming, Hydrogen Combustion, Energy Management

Abstract

The paper presents model-based scenario analyses of micro and mild tri-hybrid vehicle configurations, related to existing conventional vehicles equipped with small power proton exchange membrane (PEM) fuel cell (FC) systems and, eventually, additional battery pack. The analyses are intended to support short- to medium-term development of fuel cell powered Light Duty Vehicles (LDVs) technology and are useful for carmakers to quantitatively assess the potential advantages associated to the afore-mentioned opportunities in terms of short-term clean and cost-efficient production of hydrogen. The analyses are performed making use of a comprehensive vehicle model, based on a hybrid (black-box and lumped parameters) approach, of a medium passenger car equipped with a turbocharged SI engine. The model has been enhanced to account for the additional components of two different powertrain configurations, namely conventional powertrain with ICE and fuel cell Auxiliary Power Unit (APU) and hybrid powertrain ICE/FC. Simulations have been carried out vs. standard driving cycles for two energy management strategies. The results allow evaluating the impact of powertrain configuration on CO2 emissions, in case of both Tank-to-Wheel (TTW) and Well-to-Wheel (WTW) analyses.

 

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