Surplus Driving Range Estimation for Electric Vehicles Based on Fuzzy Energy Consumption and Kalman Filter
Journal Title: 河南科技大学学报（自然科学版） - Year 2017, Vol 38, Issue 1
Abstract
In order to improve the estimation accuracy of electric vehicle driving range,a new model of surplus driving range estimation by combining fuzzy energy consumption and Kalman filter was proposed based on condition identification. Firstly,vehicle energy consumption model was established. Then the fuzzy rule library about the characteristic parameters and energy consumption was established with the MATLAB / Simulink.Finally,the output of surplus driving range was optimized based on the Kalman filter. The experimental results show that by using this method the average error of actual mileage value to expectation is 2. 11%. The estimation accuracy of surplus driving range is improved by 77% compared with the traditional average energy consumption method.
Authors and Affiliations
Liao CHEN, Mingwei XIE, Chaofeng PAN
Keywords
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