May 16, 2013
Estimation of fuel consumption using an acoustic signal and multi-sensing signals of smartphone
IEICE technical report. Signal processing
- ,
- ,
- Volume
- 113
- Number
- 28
- First page
- 1
- Last page
- 6
- Language
- Japanese
- Publishing type
- Publisher
- The Institute of Electronics, Information and Communication Engineers
Fuel-consumption meters are equipped with many vehicles, however, they can only show the fuel-consumption/-efficiency value but not allow to use for other purpose, e.g., gathering, analyzing, etc. One of a method to output vehicles data is to use a diagnostic connector having compliant with OBD2 standards, that can output several vehicles' signals, such as, velocity, revolution of engine, and fuel consumption. However, because the protocols depend on manufactures or types of the vehicles, the method is not easy to use for the public. In this study, we aim to estimate the fuel consumption using acoustic signals and several sensor's signals equipped with a smartphone. An estimation of a number of revolutions of engine and an estimation of torque are needed for the estimation of fuel consumption. For the estimation of the number of revolutions, we analyze the acoustic signals from the engine by fast Fourier transform and calculate the estimation value from acoustic signal reducing road-noise approximated as a Gamma mixture distribution. For the estimation of the torque, we use physics of the car with the outputs of several sensors and the vehicle's data. We finally get the fuel consumption refer to a table of fuel-consumption rate, which is created in advance, by the estimated number of revolutions and the estimated torque. As a result of a experiment for the estimation of fuel-consumption, we can achieved a acceptable values of instantaneous fuel consumption, although values of average fuel comsumption have some errors.
- Link information
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- CiNii Articles
- http://ci.nii.ac.jp/naid/110009768313
- CiNii Books
- http://ci.nii.ac.jp/ncid/AA11943613
- URL
- http://id.ndl.go.jp/bib/024577915
- ID information
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- ISSN : 0913-5685
- CiNii Articles ID : 110009768313
- CiNii Books ID : AA11943613