Browse Publications Technical Papers 2022-37-0011

Experimental Assessment of Powertrain Components and Energy Flow Analysis of a Fuel Cell Electric Vehicle (FCEV) 2022-37-0011

European Union's (EU) Climate Law sets a legally binding target of net-zero greenhouse gas emissions by 2050. EU identified hydrogen technologies as a priority introducing hydrogen-powered propulsion systems into the market. Even though the new registrations of fuel cell (FC) passenger cars increased by 41% in 2020 in Europe, the research community faces a lack of public and independent available data regarding the performance and energy efficiency of state-of-the-art FC electric vehicles. This study introduces a tailored methodology to characterise the different powertrain components and analyse the energy flow for a Fuel Cell Electric Vehicle (FCEV) already available on the market. Experimental data are gathered over different driving conditions, including standard driving cycles such as WLTP and US06 tests performed in a laboratory. The acquired signals are a combination of data coming from Controller Area Network (CAN)-bus protocol, On-Board Diagnostic system (OBD) and dedicated sensors placed on the High Voltage (HV) electric network. The characteristic curves of the FC stack and the HV battery are determined along with the energy flow conditions for multiple scenarios. The measured FC stack peak efficiency of 63% is in line with data available in the literature. The powertrain performance is analysed in terms of contributions to the propulsion by the FC and the battery systems. Moreover, the interaction between the powertrain components during various driving conditions is presented and it was found that the FCEV operates as a conventional HEV where the FC behaves like the main contributor: it is shut down or idled at low speed/loads below 10 km/h and always on above 90 km/h. The HV battery works in a typical 40 - 68% SOC range, from 35kW in charging mode to −40kW in discharging mode. Finally, the information collected are used as a valuable dataset for the development of analytical tools to support the energy transition.


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