# Clutch Pressure Plate Temperature Prediction Based on Bi-LSTM and Migration Learning
## 3 Pressure Plate Temperature Prediction
### Valeo Clutch Pressure Plate Temperature Prediction  
The present study employs a novel Valeo clutch-based model for predicting the temperature of the clutch pressure plate. Initially, the pressure plate temperature from 840-870 s is used as the prediction target and predicted using the model. Subsequently, this predicted temperature is utilized as an input parameter to forecast the pressure plate temperatures for the consecutive periods of 870-900 s and 900-930 s. Finally, experiments were carried out on the platen to collect experimental data for the three time periods and analyzed for comparison. The comparison results are presented in Table 7. The temperature profiles at three different locations of the platen for 840-930 s are shown in Figure 10.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Position Indicator** & **Indicators** & **840–870 s** & **870–900 s** & **900–930 s** \\ \hline \multirow{6}{*}{a} & _MSE_ & 7.5532 & 3.8834 & 6.9621 \\  & _RMSE_ & 2.7483 & 1.9706 & 2.6386 \\  & _MAE_ & 2.6688 & 1.5129 & 2.5404 \\  & _R_\({}^{2}\) & 0.8228 & 0.9061 & 0.8677 \\  & Maximum error & 8.4339 & 7.3884 & 8.2016 \\  & Maximum relative error & 3.17\% & 2.78\% & 3.07\% \\ \hline \multirow{6}{*}{b} & _MSE_ & 0.9820 & 0.9668 & 1.1100 \\  & _RMSE_ & 0.9909 & 0.9833 & 1.0536 \\  & _MAE_ & 0.7743 & 0.6689 & 0.7746 \\  & _R_\({}^{2}\) & 0.9757 & 0.9754 & 0.9774 \\  & Maximum error & 6.1817 & 7.1541 & 9.5811 \\  & Maximum relative error & 2.26\% & 2.61\% & 3.48\% \\ \hline \multirow{6}{*}{c} & _MSE_ & 0.6269 & 0.7059 & 0.6781 \\  & _RMSE_ & 0.7918 & 0.8402 & 0.8235 \\ \cline{1-1}  & _MAE_ & 0.6994 & 0.5904 & 0.7032 \\ \cline{1-1}  & _R_\({}^{2}\) & 0.9845 & 0.9820 & 0.9862 \\ \cline{1-1}  & Maximum error & 4.7443 & 3.8167 & 3.2974 \\ \cline{1-1}  & Maximum relative error & 1.93\% & 1.54\% & 1.33\% \\ \hline \hline \end{tabular}
\end{table}
Table 6: The prediction indexes of Fuda clutch pressure plate.  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Time (s)** & _MSE_ & _RMSE_ & _MAE_ & _R_\({}^{2}\) & **Maximum Error** & **Maximum Relative Error  
From Table 7 and Figure 10, the model predicted \(R^{2}\) above 0.95 in all three cycles, with the maximum error at 840-870 s with a parameter of 6.92 \({}^{\circ}\)C and a maximum relative error of 2.08%. The average maximum error was 5.94. Analysis of the images reveals that the actual temperature drops at position b from 840-900 s and at positions a and b from 900-930 s and was faster than predicted after 6 s. The actual temperature drop at position b at 840-900 s and at positions a and b at 900-930 s was faster than predicted. The predicted errors for the three positions of the platen during the time interval of 840-930 s exhibit a high degree of consistency, with variations of less than 10 \({}^{\circ}\)C among them.  
Table 8 shows the specific metrics for the three positions of the platen in different cycles (one cycle of 30 s).  
Figure 10: Comparison of experimental values and predicted values at different time points of Valeo pressure plate: (**A**) 840–870 s; (**B**) 870–900 s; (**C**) 900–930 s.  
Table 8 illustrates the prediction performance for different platen positions. The maximum error of a position in the time interval 900-930 s is 5.9712 \({}^{\circ}\)C, and the relative error is 1.82%. The maximum error of the b position in the time interval 870-900 s is 6.9208 \({}^{\circ}\)C, and the relative error is the largest among the three positions, which is 2.08%. The effect of the position c is the best, the maximum error is 4.8756 \({}^{\circ}\)C, and the relative error is 1.00%. According to these data, it can be shown that the method still has high accuracy for the temperature prediction of different clutch pressure plates, and the established model has strong generalization ability.