Method for predicting energy consumption of hybrid truck based on variable time domain model

Abstract

The invention discloses a method for predicting the energy consumption of a hybrid truck based on a variable time domain model, and the method comprises the steps: repeatedly operating the hybrid truck in an urban working condition at a test stage, obtaining the original operation data of the truck, carrying out the preprocessing, carrying out the classification through a k-means clustering algorithm, and generating a plurality of state segments; establishing a Makarov working condition prediction model, and providing a plurality of prediction time domains for each state segment to obtain predicted vehicle speeds in the prediction time domains; calculating and recording the actual vehicle speed of the vehicle, and selecting the prediction time domain with high prediction precision as the parameter of the state segment; in the application stage, according to the characteristic parameters of normal running of the truck, the prediction time domain corresponding to the working condition with the high matching degree in the state fragments under the cyclic working condition is found to serve as the prediction time domain under the running working condition, and energy consumption is obtained according to the Makarov working condition prediction model. According to the prediction method, timely adjustment of the prediction time domain can be realized, and the calculation burden is not increased too much while the vehicle speed in the time domain is predicted more accurately.

Description

technical field [0001] The invention belongs to the technical field of hybrid truck energy management, in particular to a model predictive energy management method in which a hybrid truck changes the prediction time domain according to actual working conditions. Background technique [0002] With the development of China's manufacturing industry and trade, the freight industry is also developing rapidly. For the purpose of energy saving, emission reduction and environmental protection, hybrid technology is more and more widely used in trucks. For hybrid trucks, the energy management strategy is one of the key technologies of this type of vehicle, which undertakes the energy distribution and torque management of the entire system, and is of great significance to the fuel economy and power performance of the truck. Because model predictive control is very suitable for solving nonlinear and uncertain problems, and can combine different optimization algorithms to find the optima...

AI Technical Summary

Problems solved by technology

The fixed predictive time-domain MPC method cannot adapt well to changes in working conditions, and it is difficult for vehicles to achieve optimal fuel economy

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