A Torque Allocation Method Based on Offline Optimization and Online Prediction

Abstract

The invention discloses an offline-optimization and online-predication torque distribution method. The offline-optimization and online-predication torque distribution method comprises the steps of when a driver is going to drive a vehicle to one destination, manually selecting a driver model first and then inputting the destination; enabling a vehicle controller to optimize a travel for a learningresult of the driver according to the selected driver model; planning a path according to a starting point and a terminal point of the travel; using the selected terminal point of the travel to obtain road condition information by using a vehicle-mounted navigation system; combining the obtained road condition information, the selected driver model and a battery SOC value to perform preliminary torque distribution optimization by using a dynamic planning method; and then using model predication control to perform dynamic real-time optimal control on the basis of a preliminary torque distribution optimization result. By carrying out further real-time optimal control on the basis of existing preliminary optimization control, the calculation amount of dynamic optimization is reduced, and meanwhile, real-time online control of fuel economy of a hybrid automobile is realized.

Description

technical field [0001] The invention belongs to the field of hybrid electric vehicles, and in particular relates to a torque distribution method in mode switching. Background technique [0002] In recent years, with the rapid development of the automobile industry, the number of automobiles has continued to increase, and the pressure of the environment and energy crisis has intensified. The popularization and promotion of new energy automobile technology is one of the effective ways to solve environmental and energy problems in our country. As a key link in the transition from traditional vehicles to pure electric vehicles in new energy technology, hybrid vehicles have both internal combustion engines and batteries as on-vehicle energy sources, making them have better fuel economy and emission performance and relatively pure The advantage of longer mileage of electric vehicles shows great application potential, and has become a hot research topic in the field of automobiles ...

AI Technical Summary

Problems solved by technology

However, this strategy does not consider the dynamic changes of the actual road conditions and the influence of factors such as the efficiency of the motor, battery, and drive train, so it cannot achieve the overall optimum and the highest fuel economy of the vehicle. Therefore, further research is needed on the control strategy. Complete

From the perspective of control effect, the global optimization control method with the lowest overall fuel consumption or the highest efficiency for a specific driver's driving habits and driving conditions in the future can be regarded as the most ideal or most fuel-saving optimization of the hybrid system. method, but it is necessary to collect the driving habits of the driver in advance, and obtain the road condition information in the future by means, but the calculation is huge and cannot be directly used for real-time control of the real vehicle, but it can be used as an evaluation standard in the energy management design stage. Provide some necessary reference information for real-time control

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