Abstract

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.

Highlights

  • Plug-in hybrid electric vehicles (PHEVs) can take advantage of both external electrical energy and hybrid powertrain to reduce fuel consumption (FC)

  • This paper focuses on light-duty PHEVs, including sedans and sports utility vehicles (SUVs)

  • The following conclusions are basically obtained: (1) The first-ranked sales PHEV models in China and the US markets are both sedans with first-ranked FC and FC2CW, (2) Among the models with the top five sales of two countries, the types and sales of SUVs in China, whose fuel economy are not very good, are significantly more than that in the US, and (3) The fuel economy rankings of the models with the top five sales in the US are relatively better than that in China

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Summary

Introduction

Plug-in hybrid electric vehicles (PHEVs) can take advantage of both external electrical energy and hybrid powertrain to reduce fuel consumption (FC). Several typical hybrid systems that have a large market share might be the focusing points [37], for instance, Toyota Hybrid System (THS) [38], Honda Intelligent Multi Mode Drive (IMMD) [39], General Motor two modes [40], etc In these studies of numerous architectures, three problems exist: Firstly, there is a lack of a unified classification method to characterize the specific structure of the hybrid powertrain. Most of the research has been based on the optimization theory to compare architectures and lacked test performance comparison on the actual market When comparing analysis, they mainly used the simulation method, maintaining the same dynamic property and all electric range (AER) under the same driving cycle, adopting the global optimization algorithm, and comparing the energy consumption. Market conditions [9]; Market-related policies [10]; Costs [11,12,13]; Choices of market subjects [14]

Method
Development Trend
Composition Characteristics
Classification Method
Architectures of Models
Proposition of Mainstream Architectures
Multi-Dimensional Comparative Analysis
Analysis of PHEV Testing Performance
Comparison of Testing Methods
Fuel Consumption of Models
Fuel Consumption Distribution Characteristics
Fuel Consumption of Architectures
Curb Weight Analysis
All Electric Range Analysis
Findings
Conclusions
Full Text
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