Develop of a fuel consumption model for hybrid vehicles

2020 ◽  
Vol 207 ◽  
pp. 112546 ◽  
Author(s):  
Yan-Tao Zhang ◽  
Christian G. Claudel ◽  
Mao-Bin Hu ◽  
Yu-Hang Yu ◽  
Cong-Ling Shi
2019 ◽  
Vol 10 (2) ◽  
pp. 22 ◽  
Author(s):  
Siriorn Pitanuwat ◽  
Hirofumi Aoki ◽  
Satoru IIzuka ◽  
Takayuki Morikawa

In the transportation sector, the fuel consumption model is a fundamental tool for vehicles’ energy consumption and emission analysis. Over the past decades, vehicle-specific power (VSP) has been enormously adopted in a number of studies to estimate vehicles’ instantaneous driving power. Then, the relationship between the driving power and fuel consumption is established as a fuel consumption model based on statistical approaches. This study proposes a new methodology to improve the conventional energy consumption modeling methods for hybrid vehicles. The content is organized into a two-paper series. Part I captures the driving power equation development and the coefficient calibration for a specific vehicle model or fleet. Part II focuses on hybrid vehicles’ energy consumption modeling, and utilizes the equation obtained in Part I to estimate the driving power. Also, this paper has discovered that driving power is not the only primary factor that influences hybrid vehicles’ energy consumption. This study introduces a new approach by applying the fundamental of hybrid powertrain operation to reduce the errors and drawbacks of the conventional modeling methods. This study employs a new driving power estimation equation calibrated for the third generation Toyota Prius from Part I. Then, the Traction Force-Speed Based Fuel Consumption Model (TFS model) is proposed. The combination of these two processes provides a significant improvement in fuel consumption prediction error compared to the conventional VSP prediction method. The absolute maximum error was reduced from 57% to 23%, and more than 90% of the predictions fell inside the 95% confidential interval. These validation results were conducted based on real-world driving data. Furthermore, the results show that the proposed model captures the efficiency variation of the hybrid powertrain well due to the multi-operation mode transition throughout the variation of the driving conditions. This study also provides a supporting analysis indicating that the driving mode transition in hybrid vehicles significantly affects the energy consumption. Thus, it is necessary to consider these unique characteristics to the modeling process.


2021 ◽  
Author(s):  
Stijn Broekaert ◽  
Evangelos Bitsanis ◽  
Georgios Fontaras

2019 ◽  
Vol 1 (1) ◽  
pp. 472-480 ◽  
Author(s):  
Máté Zöldy ◽  
Imre Zsombók

AbstractDuring our research, we focus on a less researched area in the development of autonomous vehicles. Automotive industry is turning more and more from conventional, internal combustion engine equipped vehicles to the electric cars. Today, electric driving is mostly limited to urban traffic, this is the area where range and refueling limits can be a real alternative. However, it is important to think of those who intend to use vehicle in longer distances, and hybrid technology can provide them a modern, environmentally conscious way of transport.In this article, we describe the method of creating the fuel consumption influencing factors matrix, which is the starting point of our research. We studied relevant researches and based on refueling studies we created the matrix. Based on results of real tests, we determined the factor mix that are the basis of our fuel consumption prediction model. These results will be inputs of planning routes of autonomous vehicles with optimized refueling and fuel consumption.


Author(s):  
Jony J. Eckert ◽  
Fabio M. Santiciolli ◽  
Ludmila C. A. Silva ◽  
Eduardo S. Costa ◽  
Fernanda C. Corrêa ◽  
...  

2020 ◽  
Author(s):  
Patrick Phlips ◽  
William Ruona ◽  
Thomas Megli ◽  
Mrudula Orpe

2013 ◽  
Vol 38 (13) ◽  
pp. 5192-5200 ◽  
Author(s):  
C.H. Zheng ◽  
N.W. Kim ◽  
Y.I. Park ◽  
W.S. Lim ◽  
S.W. Cha ◽  
...  

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