Energy Consumption Estimation in Electric Vehicles Considering Driving Style

The limitation on the range of electric vehicles makes quite important to use an accurate energy consumption estimation tool. In general, estimations are based solely on the total distance, although it is known that the characteristics of the route and driving style influence significantly on energy consumption. In this paper, a tool that estimates the energy consumption of an electric vehicle in a city route taking into account such variables is shown, but without needing a deterministic knowledge of the characteristics of the vehicle or driving cycles. To do this, a neural network that takes as input data driving style and route variables is used. The validation results have been quite satisfactory to increase reliability in predicting consumption of the vehicle and enhance user confidence in the capabilities of electric vehicles.

[1]  Felipe Jiménez Alonso,et al.  Simulation and testing of hybrid vehicle function as part of a multidisciplinary training , 2011, Comput. Appl. Eng. Educ..

[2]  Jean Andrey,et al.  Eco-driver training within the City of Calgary's municipal fleet: Monitoring the impact , 2013 .

[3]  Manohar Das,et al.  Driver Classification for Optimization of Energy Usage in a Vehicle , 2012, CSER.

[4]  Toshihiro Hiraoka,et al.  Quantitative Evaluation of Eco-Driving on Fuel Consumption Based on Driving Simulator Experiments , 2009 .

[5]  Carmen Sánchez Ávila,et al.  Modeling and Detecting Aggressiveness From Driving Signals , 2014, IEEE Transactions on Intelligent Transportation Systems.

[6]  Robert B. Noland,et al.  Current map-matching algorithms for transport applications: State-of-the art and future research directions , 2007 .

[7]  Gonçalo Duarte,et al.  Vehicle monitoring for driver training in bus companies - Application in two case studies in Portugal , 2013 .

[8]  Felipe Jiménez Alonso,et al.  Estimación de la autonomía de un vehículo eléctrico según el estilo de conducción , 2015 .

[9]  José Eugenio Naranjo,et al.  Limitations of Positioning Systems for Developing Digital Maps and Locating Vehicles According to the Specifications of Future Driver Assistance Systems , 2011 .

[10]  José Eugenio Naranjo,et al.  Modeling the Driving Behavior of Electric Vehicles Using Smartphones and Neural Networks , 2014, IEEE Intelligent Transportation Systems Magazine.

[11]  José María Cuenca López,et al.  Methodology for kinematic cycle characterization of vehicles with fixed routes in urban areas , 2013 .

[12]  José Eugenio Naranjo,et al.  GPS and Inertial Systems for High Precision Positioning on Motorways , 2009, Journal of Navigation.