China and the US have become the world's largest plug-in hybrid electric vehicle (PHEV) markets. Powertrain architecture is the framework of PHEV technology which represents its technical route. The research on the market development and technical route of Chinese and American PHEV is helpful to grasp the internal law of the global PHEV market and technology situation, and thus is significant to lay out a development strategy and technical route but has not been sufficiently studied. Therefore, an evaluation method of three dimensions combining market sales, powertrain architectures and performance indexes was proposed for comparative analysis, and PHEV mainstream architectures were put forward. Besides, qualitative evaluation levels from nine dimensions were built for architecture analysis, and fuel consumption to curb weight (FC2CW) as an indicator was introduced for economy evaluation. Some conclusions can be drawn: (a) The most mainstream architecture in sales volume is four-wheel drive (4WD) Bridge, and that in models’ amount is P2 in China, while those respectively are PS and P2 in the US. This reflects that a difference exists between the choice of the consumers and that of the automakers, and another difference also exists between the two countries. (b) With the phasing down of subsidies, the single-motor parallel architecture may become the first choice of China's next technical route, while the 4WD Bridge will still be the main architecture for sports utility vehicles (SUVs) or sports car. (c) Among the models of the top five sales, the types and sales of SUVs in China are significantly more, however, the fuel economy rankings of theirs in the US are relatively better. (d) It is difficult to distinguish which architecture has the absolute best economy, but the fuel economy of the series type in the two markets is not very good.
The series hybrid electric powertrain is the main architecture of the hybrid electric tracked vehicle. For a series tracked hybrid electric bulldozer (HEB), frequent fluctuations of the engine working points, deviation of the genset working points from the pre-set target trajectory due to an insufficient response, or interference of the hydraulic pump consumed torque, will all result in increased fuel consumption. To solve the three problems of fuel economy, an adaptive smooth power following (ASPF) control strategy based on an optimal efficiency map is proposed. The strategy combines a fuzzy adaptive filter algorithm with a genset’s optimal efficiency, which can adaptively smooth the working points of the genset and search the trajectory for the genset’s best efficiency when the hydraulic pump torque is involved. In this study, the proposed strategy was compared on the established HEB hardware in loop (HIL) platform with two other strategies: a power following strategy in a preliminarily practical application (PF1) and a typical power following strategy based on the engine minimum fuel consumption curve (PF2). The results of the comparison show that (1) the proposed approach can significantly reduce the fluctuation and pre-set trajectory deviation of the engine and generator working points; (2) the ASPF strategy achieves a 7.8% improvement in the equivalent fuel saving ratio (EFSR) over the PF1 strategy, and a 3.4% better ratio than the PF2 strategy; and (3) the ASPF strategy can be implemented online with a practical controller.
Driving cycles have been developed for various types of vehicle by different nations and in different areas, as they have a substantial effect on analysis of the fuel economy and the emissions. As the concern about the fuel consumption and the emissions of engineering machinery increases continuously, it has become necessary to develop corresponding operation cycles for engineering machinery. However, a typical operation cycle for bulldozers and the methods for its development is still lacking. Therefore, a representative operation cycle for bulldozers was developed in this study. By taking advantage of readily available data from the Controller Area Network (CAN), large amounts of cycle experimental data were acquired in a typical bulldozing process. Two parameters, namely the bulldozing resistance and the speed, were employed to represent the operation cycle. The values of these parameters were calculated on the basis of the dynamic model and the kinematic model combined with system identification methods. Experimental cycles were divided into operation segments according to the respective operating processes, and characteristic parameters for the operation segments were chosen and calculated accordingly. The optimal representative operation cycle was finally selected on the basis of the smallest Mahalanobis distance. The fuel consumption and the probability distributions of the representative operation cycle were also compared with the average fuel consumption and probability distributions of all the operation cycles and analysed. The average correlation coefficient of the probability distributions was 0.936, whereas the difference in the fuel consumptions was only 1.786%. This indicates that the developed cycle is indeed appropriate for representing the operating process of the bulldozer.
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