As fossil fuels continue to be extracted and used, issues such as environmental pollution and energy scarcity are surfacing. For the transportation industry, the best way to achieve the goal of “carbon neutrality” is to research efficient power systems and develop new alternative fuels. As the world’s largest product of chemicals, ammonia is a new renewable fuel with good combustion energy. It can be used as an alternative fuel to reduce carbon emissions because of its proven production process, low production and transportation costs, safe storage, the absence of carbon-containing compounds in its emissions, and its future recyclability. This paper firstly introduces the characteristics of ammonia fuel engine and its problems; then it summarizes the effects of various ammonia-blended fuels on the combustion and emission characteristics of the engine from the combustion problem of ammonia-blended engine; then the fuel storage of ammonia-blended hydrogen is discussed, the feasibility of hydrogen production instead of hydrogen storage is introduced.

There are still many unsolved mysteries in the thermal decomposition process of urea. This paper studied the thermal decomposition process of urea at constant temperatures by the thermal gravimetric–mass spectrometry analysis method. The results show that there are three obvious stages of mass loss during the thermal decomposition process of urea, which is closely related to the temperature. When the temperature was below 160 °C, urea decomposition almost did not occur, and molten urea evaporated slowly. When the temperature was between 180 and 200 °C, the content of biuret, one of the by-products in the thermal decomposition of urea, reached a maximum. When the temperature was higher than 200 °C, the first stage of mass loss was completed quickly, and urea and biuret rapidly broke down. When the temperature was about 240 °C, there were rarely urea and biuret in residual substance; however, the content of cyanuric acid was still rising. When the temperature was higher than 280°C, there was a second stage of mass loss. In the second stage of mass loss, when the temperature was higher than 330 °C, mass decreased rapidly, which was mainly due to the decomposition of cyanuric acid. When the temperature was higher than 380 °C, the third stage of mass loss occurred. However, when the temperature was higher than 400 °C, and after continuous heating was applied for a sufficiently long time, the residual mass was reduced to almost zero eventually.

As a complex field-circuit coupling system comprised of electric, magnetic and thermal machines, the permanent magnet synchronous motor of the electric vehicle has various operating conditions and complicated condition environment. There are various forms of failure, and the signs of failure are crossed or overlapped. Randomness, secondary, concurrency and communication characteristics make it difficult to diagnose faults. Meanwhile, the common intelligent diagnosis methods have low accuracy, poor generalization ability and difficulty in processing high-dimensional data. This paper proposes a method of fault feature extraction for motor based on the principle of stacked denoising autoencoder (SDAE) combined with the support vector machine (SVM) classifier. First, the motor signals collected from the experiment were processed, and the input data were randomly damaged by adding noise. Furthermore, according to the experimental results, the network structure of stacked denoising autoencoder was constructed, the optimal learning rate, noise reduction coefficient and the other network parameters were set. Finally, the trained network was used to verify the test samples. Compared with the traditional fault extraction method and single autoencoder method, this method has the advantages of better accuracy, strong generalization ability and easy-to-deal-with high-dimensional data features.

For the National VI heavy-duty diesel vehicles, NO_x emission regulations are becoming more and more stringent, and the selective catalytic reduction (SCR) system has become a necessary device. The design of the adblue nozzle in the SCR system is especially critical, directly affecting the NO_x conversion efficiency and deposit formation. According to the structure of a National VI diesel engine exhaust pipe and SCR system, the nozzle is optimized by computational fluid dynamics (CFD) method to avoid the collision between the urea droplets and the exhaust pipe wall, to ensure that the exhaust gas and the urea droplets are as much as possible in full contact to ensure a sufficient urea pyrolysis. With the optimized nozzle, the NH₃ distribution uniformity of the inlet face of the SCR catalyst can increase from 0.58 to 0.92. Additionally, test verifications are implemented based on the spray particle size test and the engine bench tests; the results show that the Sauter mean diameter of the optimized nozzle is more decreased than the initial nozzle and that the NO_x conversion efficiency of the World Harmonized Transient Cycle (WHTC) and World Harmonized Stationary Cycle (WHSC) cycle improves by nearly 3%; additionally, it can also avoid deposit formation.