# Automatic Failure Modes and Effects Analysis of an Electronic Fuel Injection Model
## 4 Case study: Electronic Fuel Injection System
### Electronic Fuel Injection Analysis Using Automatic FMEA
#### 4.2.4 Step 4: Fault Injection Simulation  
The final step of automatic FMEA performs fault simulation according to the failure mode scenario, as shown in Table 3. For each failure mode, the corresponding entries of the FMEA template are completed using the results of the automatic FMEA process. The three failure effects for the failure mode in the throttle position sensor (TPS) are presented in Figure 10. The local effects are measured at the TPS, the next higher effects are measured at the fuel rate controller module, and the end effects are measured at the engine RPM, to represent the status of the vehicle as shown in Figure 10--c, respectively. We performed the simulated fault injection using the fault model to represent the drift failure mode, where the input signal is reduced to 50% of the original signal and injected into the input variable at 150 s for about 1 s. The function, the mission, the three failure effects, and the severity of the drift failure mode at the throttle position sensor are summarized in Table 6. \begin{table}
\begin{tabular}{c c c c c} \hline
**No** & **Failure Effect** & **Decision Mode Option** & **Condition** & **Severity** \\ \hline
1 & Engine stop & Specific failure condition check & RPM == 0 & 8 \\
2 & Engine hesitation & Error margin values check & (RPM \(<\) 1120) \& (RPM \(>\) 1680) & 7 \\
3 & Engine hesitation & Error margin values check & (RPM \(<\) 1190) \& (RPM \(>\) 1610) & 6 \\
4 & Engine hesitation & Error margin values check & (RPM \(<\) 1260) \& (RPM \(>\) 1540) & 5 \\
5 & Engine hesitation & Error margin values check & (RPM \(<\) 1330) \& (RPM \(>\) 1470) & 4 \\
6 & Gas mileage low & Underestimation values check & _mpg_\(<\) 20 (FE 1, 2, 3) & 4 \\
7 & Gas mileage low & Underestimation values check & _mpg_\(<\) 27 (FE 4, 5) & 3 \\
8 & Gas mileage low & Underestimation values check & _mpg_\(<\) 33 (FE 6, 7) & 2 \\
9 & Gas mileage low & Overestimation values check & _mpg_\(>\) 33 (FE 8, 9, 10) & 1 \\ \hline \end{tabular}
\end{table} 
Table 5: Failure effect table for severity (RPM represents revolutions per minute, FE represents the fuel economy figure assigned by the EPA). We performed the simulated fault injection using the drift failure mode at the throttle position sensor to find the function, the mission, the three failure effects, and the severity, as shown in Table 6. The fault model was the drift failure mode, where the input signal was reduced to 50% of the original signal and injected into the input variable at 150 s to 505 s. Once this fault model was injected into the EFI model, we could find the local effect of the failure effect by monitoring the TPS, where the value of the signal fell from 13% to 6.5%, as shown in Figure 10(a). The next effect was detected at the fuel rate controller module, where the value of fuel rate dropped to 0 g/s at 150 s, as shown in Figure 10(b). Finally, the end effect was observed at the engine module, which showed a sudden drop from 1400 RPM to 0 RPM, as shown in Figure 10(c). These three pieces of information illustrate the occurrence of the event of the vehicle stop, so we can assign the severity of this failure effect to 8. Automatic FMEA can analyze the failure effects by including FMEA severity analysis using failure simulation. We performed a total of 328 fault injection simulations on four sensors in the EFI sensor unit for the drift, hard-over, and stuck failure modes, and the results are summarized in Table 7. In the table, the failure effects are grouped into three categories: engine stop, engine hesitation, and gas mileage reduction. From the table, we can show that the contributions of the four sensors to the criticality to the EFI system are different from one another. Among the four sensors, the sensor with the highest number of failures (59) was the CPS sensor. On the other hand, the EGO sensor was the most vulnerable to the critical failure effects, such as the hard-over and stuck failure effects.