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Proton exchange membrane (PEM) fuel cell is widely recognized as an outstanding portable power plant and expected to be possibly commercialization in the near future. As is well known, mechanical stresses implemented on the bipolar plates during the assembly procedure should have prominent influences on mass and heat transfer behavior inside the cell, as well as the resultant performance. In this study, an analytical model is proposed to comprehensively investigate the influence of clamping force on the mass transport, electrochemical properties and overall cell output capability of a PEM fuel cell. The results indicate that proper clamping force not only benefits the gas leakage prevention but also increases the contact area between the neighboring components to decrease the contact ohmic resistance.

Most of algorithms of lane detection mainly aim at the scenes of daytime. However, those algorithms are unstable for the lane detection at night because the camera is very sensitive to the light change. This paper proposed a lane detection algorithm that largely improves the detection system’s performance when it is used at night. The algorithm has two main stage: Image processing and Kalman filter (KF). The key process steps of Stage 1 are: extracting the Region of Interesting (ROI)→Edge Detection →Binarization→Hough→ Lane Selection→Lane fitting. First step, a ROI could be extracted according to the relatively fixed location of lanes. In step of edge detection, we use a creative filter named Correlation filter to remove image noise and remain the feature of lane. The filter matrix looks like “[0 1 1, −1 0 1; −1 −1 0]”. Next, the candidate lines are detected by the Hough transform, then, the equations of lane are acquired by fitting spots obtained from Hough.

By installing an automated mechanical transmission (AMT) on heavy-duty vehicles and developing a reasonable shift strategy, it can reduce driver fatigue and eliminate technical differences among drivers, improving vehicle performance. However, after detaching from the experience of good drivers, the current shifting strategy is limited to the vehicle state at the current moment, and cannot make predictive judgment of the road environment ahead, and problems such as cyclic shifting will occur due to insufficient power when driving on the ramp. To improve the adaptability of heavy-duty truck shift strategy to dynamic driving environments, this paper first analyzes the shortcomings of existing traditional heavy-duty truck shift strategies on slopes, and develops a comprehensive performance shift strategy incorporating slope factors. Based on this, forward-looking information is introduced to propose a predictive intelligent shift strategy that balances power and economy.