Quantitative Evaluation of Energy-saving Driving Based on Wavelet Transform

With the rapid growth of the automobile industry, the issues of energy consumption and exhaust emissions have become increasingly significant. Addressing the energy consumption of fuel vehicles, a quantitative evaluation on energy-saving driving on vehicles was conducted in this study. Two sets of data, comprising 16,350 and 19,269 frames respectively, were collected using the OBD-II sensor, which included various road conditions, such as campuses, cities, and highways. This study proposes a method based on wavelet transform to extract the volatility characteristic of automobile driving signals, namely speed, acceleration, and jerk, allowing for the description of driving behavior using the volatility characteristic index. A quantitative evaluation of energy-saving driving was conducted. In the experiment, the mean filtering method was used to simulate the driving conditions of different degrees of fluctuation, and the Vehicle Specific Power (VSP) model was used to calculate the cumulative fuel consumption for each working condition. The experimental results demonstrate a positive correlation between the volatility characteristic index of the driving signal and vehicular fuel consumption, suggesting that the index can serve as a quantitative description of the fuel economy of the driving behavior.