Real-Time Prediction of Fuel Consumption Based on Digital Map API

Qi Zhao,Li Wang,Qi Chen

doi:10.3390/app9071369

Abstract

At present, digital maps can estimate the travel time of each trip’s route but cannot offer a fuel consumption estimation at the same time. In this paper, we develop a fuel consumption model based on the Vehicle Specific Power (VSP) distribution, which can connect the traffic condition prediction with the fuel consumption model to predict fuel consumption. First, the traffic condition forecasting and the trip time of each route can be obtained through the digital map Application Programming Interface (API). Secondly, the users need to provide the engine displacement of their vehicles to match the fuel consumption model. Then, the fuel consumption prediction application based on Android is developed to forecast the fuel consumption by using traffic prediction data. Finally, the fuel consumption provided by the On-Board Diagnostic (OBD) data is used to verify the proposed application, and the forecasting error is less than 20%.

Highlights

With the development of digital maps and mobile internet, drivers rely increasingly on route guidance services, which can tell drivers the predicted trip time of each route
The aim of this study is to develop a fuel consumption prediction model by combining digital maps with traditional fuel consumption models
According to the parameters which are used in fuel consumption models, the model can be classified as a fuel consumption model based on speed-acceleration statistics [4], a fuel consumption model based on operating mode decomposition [5,6] or a power demand model [7,8,9]

Summary

Introduction

With the development of digital maps and mobile internet, drivers rely increasingly on route guidance services, which can tell drivers the predicted trip time of each route. The aim of this study is to develop a fuel consumption prediction model by combining digital maps with traditional fuel consumption models. According to the parameters which are used in fuel consumption models, the model can be classified as a fuel consumption model based on speed-acceleration statistics [4], a fuel consumption model based on operating mode decomposition [5,6] or a power demand model [7,8,9]. The statistical model based on speed-acceleration is the most simple and intuitive, but the disadvantage is that it does not differentiate the vehicle operating mode, which leads to a larger error in the fuel consumption calculation. A power demand parameter, Vehicle Specific Power (VSP), based on vehicle speed and acceleration, has been developed and can be used to describe the power of the vehicle

Objectives

Methods

Findings

Conclusion