Virginia Tech Comprehensive Power-Based Fuel Consumption Model: Model development and testing

2011 ◽  
Vol 16 (7) ◽  
pp. 492-503 ◽  
Author(s):  
Hesham A. Rakha ◽  
Kyoungho Ahn ◽  
Kevin Moran ◽  
Bart Saerens ◽  
Eric Van den Bulck
Keyword(s):  
Fuel Consumption ◽  
Model Development ◽  
Virginia Tech ◽  
Consumption Model

Modeling Diesel and Hybrid Bus Fuel Consumption with Virginia Tech Comprehensive Power-Based Fuel Consumption Model: Model enhancements and Calibration issues

2015 ◽  
Vol 2533 (1) ◽  
pp. 100-108 ◽  
Author(s):  
William Edwardes ◽  
Hesham Rakha
Keyword(s):  
Fuel Consumption ◽  
Field Data ◽  
Mean Squared Error ◽  
Carbon Dioxide Emission ◽  
Calibration Procedure ◽  
Virginia Tech ◽  
Coefficient Of Determination ◽  
Average Error ◽  
Model Parameters ◽  
Consumption Model

The goal of this paper was to develop a calibration procedure and use it to estimate diesel bus fuel consumption and carbon dioxide emission levels. There are few models for estimating those values. Available models require dynamometer data to calibrate model parameters and produce a bang-bang control system (optimum control entails maximum throttle and braking input). The only diesel fuel consumption model that does not suffer from these deficiencies is the Virginia Tech comprehensive power-based fuel consumption model (VT-CPFM). VT-CPFM can be calibrated with publicly available data from the Altoona Bus Research and Testing Center. However, each bus is slightly different because it is built and tuned for the specific transit agency. Consequently, research presented in this paper enhanced the VT-CPFM for modeling diesel buses and developed a procedure for calibrating bus fuel consumption models by using in-field data. All models produced a good fit to the in-field data with a coefficient of determination ( R2) greater than .936, and the sum of the mean squared error for each quarter of a second was less than 0.002. Validation found an average error of 17.55% in total fuel consumed during the validation portion of the test. However, for tests with air-conditioning on, the average error was 10.82%.

A Simplified CO2 and Fuel Consumption Model for Buses Derived from VECTO Simulations

2021 ◽  
Author(s):  
Stijn Broekaert ◽  
Evangelos Bitsanis ◽  
Georgios Fontaras
Keyword(s):  
Fuel Consumption ◽  
Consumption Model

scholarly journals Development of Hybrid Vehicle Energy Consumption Model for Transportation Applications—Part II: Traction Force-Speed Based Energy Consumption Modeling

2019 ◽  
Vol 10 (2) ◽  
pp. 22 ◽  
Author(s):  
Siriorn Pitanuwat ◽  
Hirofumi Aoki ◽  
Satoru IIzuka ◽  
Takayuki Morikawa
Keyword(s):  
Energy Consumption ◽  
Fuel Consumption ◽  
Traction Force ◽  
Hybrid Vehicles ◽  
Specific Power ◽  
Mode Transition ◽  
Hybrid Powertrain ◽  
Modeling Methods ◽  
Consumption Model ◽  
Energy Consumption Modeling

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.

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