Vehicle Fuel Consumption Estimation Method Based On Mobile Terminal Sensor Data

mastering the fuel consumption of the vehicle in real time is the key to study the assistant technology of ecological driving and reduce fuel consumption and exhaust emissions.Although the instantaneous fuel consumption can be accurately obtained through the internal sensors of the car,this method needs to obtain private protocols for different models of cars and install corresponding OBD equipment,which limits its applicability.Intelligent mobile terminals have been more and more widely used,and a lot of sensors have been installed inside them,which makes it possible to use the mobile terminals to detect the acceleration and speed of the car,and then estimate the fuel consumption in real time.Therefore,it is of great practical significance to improve the fuel economy by making full use of the sensor data of the intelligent mobile terminal to establish a more reliable and accurate method for estimating the fuel consumption in real time.Based on the mobile terminal sensor data,this paper studies the road slope estimation and acceleration correction model to resolve the problem of acceleration sensor data with random noise and gravity components,and then aiming at the velocity cumulative error caused by acceleration integral,a correction method combining reference point with GPS is proposed.Finally,based on acceleration and speed,and considering the impact of road slope,a fuel consumption model was established to estimate driving fuel consumption in real time.Research work of this paper includes the following three aspects:Firstly,based on the collected acceleration sensor and gyroscope data,a slope estimation and acceleration correction model based on adaptive Kalman fusion filter is established.Real vehicle experiments show that the algorithm can filter the acceleration data effectively and remove the influence of gravity components.Secondly,by analyzing the cumulative error of velocity and aiming at the problem that the accuracy of velocity estimation will be greatly reduced when the reference points are few,a velocity correction method combining reference points and GPS is established.The experimental results show that the proposed method is better than the existing method when the reference points are few.Thirdly,research shows that road slope has a great influence on vehicle fuel consumption,but it is difficult to obtain real-time road slope,so few studies considerthis factor in estimating fuel consumption.In this paper,Based on the estimation of vehicle acceleration,speed and road gradient,a PB fuel consumption model is established to estimate fuel consumption in real time.The real vehicle comparison experiment shows that the fuel consumption model considering slope can better describe the fuel consumption of the vehicle.In summary,based on mobile terminal sensor data,this paper establishes an estimation method of vehicle driving acceleration and speed,and on this basis,establishes a fuel consumption model to realize real-time estimation of fuel consumption.The experimental results show that the proposed method can correctly estimate the fuel consumption of the vehicle,and the estimation accuracy can meet the practical application requirements.