Risk Analysis on a Fuel Cell in Electric Vehicle Using the MADS/MOSAR Methodology

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Abstract

Fuel cells are processes of electric and thermal energy production which can be used for electric vehicles. They deliver strong power densities and do not require load time as batteries do. However, the use of fuel cells introduces strong constraints related to their different parts: feed systems, conversion and storage of fuel (hydrogen or methanol), management of the produced energy either under electric or thermal form, discharge of exhaust gases. The risk analysis presented in this paper consists of forecasting and minimizing undesired events that could occur when a fuel cell is powering an electric vehicle. This study refers to electric vehicles based on relevant fuel feeds (e.g., hydrogen or methanol). The MADS/MOSAR methodology is used. Five scenarios of accident are highlighted, leading to jet flame, BLEVE, internal combustion, unconfined explosion and environmental pollution. They are evaluated and prioritized by using Severity versus Probability grid. The main risk in terms of both severity and probability is related to fuel handling that can be nevertheless limited by using prevention and protection barriers. Due to the low durability of the electrolyte, the risk of electrolyte failure can be also very important.

Introduction

Research to reduce pollutant emissions resulted in considering the use of innovating technologies for electric energy production. Within this framework, fuel cells have made considerable strides in many energy sectors from a few kilowatts (electric vehicle) to several megawatts (stationary applications with co-generation) (Larminie and Dicks, 2000). However, technological obstacles still remains related not only to materials but also to the dynamic behaviour, the safety and the reliability of these systems, so limiting their development (Adamson and Pearson, 2000, Junker et al., 2001). Indeed, energy production requires a continuous fuel feed, e.g., hydrogen, methanol, gasoline and methane (Chalk et al., 2000), and oxygen. Hydrogen fuel, stored or produced in situ by reforming, must offer a level of safety and facility of handling equivalent to traditional fuels.

The application of fuel cells to electric vehicles requires being able to provide vehicles offering the same performances and the same comfort as non-electric vehicles. The choice of the fuel remains a real challenge with various aspects involving reformer technology, emissions and safety (Ogden et al., 1999). The most vehicle prototypes are equipped with Proton Exchange Membrane Fuel Cells (PEMFC) working at low temperature (<80°C) and supplied with hydrogen fuel (Büchel et al., 2001). Using hydrogen then implies its storage or its production on board, generally by reforming from methanol or gasoline (Adamson and Pearson, 2000).

The aspects of safety, and the feelings of potential users about it largely depend on the fuel nature (Adamson and Pearson, 2000). For hydrogen, which is much lighter than air, studies have shown that its dispersion avoids any risk of reaching the lower flammability limit in an unenclosed environment whereas this problem may occur with methane. However, the situation becomes very different regarding confined surroundings (tunnel, garage and especially inside the vehicle) wherein this threshold value can be reached. Methanol and gasoline present similar properties and the fire risk from fuel slicks remain dominant (Adamson and Pearson, 2000). Moreover, the toxicity of methanol could lead to serious health concerns or even ground pollution in the event of uncontrolled flowing.

A key phase of a risk analysis is the selection of a corresponding risk model. The risk analysis presented in this paper consists of forecasting and minimizing undesired events that could occur when a fuel cell is operating in an electric vehicle; it uses the MADS/MOSAR methodology. MADS refers to ‘the analysis method of dysfunctional systems’, and MOSAR refers to ‘the organized and systemically method of risk analysis’. MADS proposes a general model of hazard, MOSAR builds a global methodology for the risk analysis (Périlhon, 2000, Rogers, 2000). The first step is the system identification and the subsequent steps are to formulate the provisions that would be lead to an increase in the vehicle safety; the solution for this task requires the following:

  • to define the hazard sources. This step can be done with a basic list, defined by Périlhon (Périlhon, 2000) based on the return of experience (REX), it is structured in hazard typologies according to the MADS model;

  • to find the spectrum of initiating events that may disturb the technological process, i.e., may develop an incident;

  • to develop these initiating events into event scenarios;

  • to evaluate and prioritize the likelihood and consequences of event scenarios considered, those steps can be perform using a Severity versus Probability grid;

  • to define the means (barriers) of prevention and/protection in order to reduce the risks.

From the 62 risks analysis methodologies identified by Tixier et al. (2002), the MADS/MOSAR quantitative method includes both deterministic and probabilistic approaches. The implementation of the MADS/MOSAR method requires plans and diagrams related to the site, installations, units and fluids networks. For these reasons, this method is well-appropriated to our risk analysis.

Section snippets

Structure of Fuel Cell Systems

Fuel cells are electrochemical devices that convert the chemical energy of a reaction directly into electric energy. Although a fuel cell produces electricity, an on-board fuel cell power system requires the integration of many components beyond the fuel cell stack itself. Various system components are incorporated into a power system to allow operation with conventional fuels, to tie into the AC power grid, and often, to utilize rejected heat to achieve high efficiency. So, a fuel cell power

Presentation of the MADS/MOSAR Method

The MADS model is a systemic approach to unfolding complex systems and evaluate the potential damage in specific targets. As shown in Figure 2, it allows to identify and to model the mechanism of hazard between sources of hazard and targets. We can conduct a study of the hazard process in which a source of hazard is linked to a target through the phenomena called ‘hazard flux’. This is done in a very specific relation called fields of hazard that takes into account space and time dimensions (

Division into Subsystems

The first stage of the MADS/MOSAR method consists of modelling the onboard fuel with its auxiliaries in electric vehicle by means of a functional division of the fuel cell and its auxiliaries into subsystems. From the previous description of the electric vehicle, we can distinguish four subsystems:

  • the fuel processing including the fuel tank, turbine/compressor and the reformer if necessary;

  • the electrical power system including the fuel cell stack, batteries and the electrical circuit;

  • the

Conclusion

A risk analysis of a fuel cell and its auxiliary is performed by using the MADS/MOSAR method. The MADS/MOSAR method appears to be a useful tool to state the scenarios of accidents, to quantify their effects and to treat them on a hierarchical basis. This analysis shows that the use of methanol storage into the electric vehicle presents associated risks equivalent to those of a traditional vehicle. For hydrogen fuel (direct or via reformer), even though the effects of an explosion lead to severe

Acknowledgement

This work was supported by the French by INRS via the ARI pedagogic network (http://www.agora21.org/ari/).

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