Network-connected hybrid electric vehicle energy management system and method of a distributed MPC

Abstract

A network-connected hybrid electric vehicle energy management system of a distributed MPC comprises an engine, a clutch, a motor, a transmission and batteries. The MCU of the motor is connected with the TCU of the transmission and the ECU of the engine; the batteries are respectively connected with the motors; the batteries transmit power to the motor; working modes comprise pure electric driving, pure engine driving, hybrid driving, driving charging and regenerative braking; the method by means of the network-connected hybrid electric vehicle energy management system comprises the following steps: 1, modeling a parallel hybrid electric vehicle; 2, predicting the speed of the networked hybrid electric vehicle; and 3, constructing a distributed MPC energy management method; the system and the method have the characteristics of good calculation efficiency, fuel economy and working condition adaptability.

Description

technical field [0001] The invention belongs to the technical field of automobiles, and in particular relates to a distributed MPC network-connected hybrid electric vehicle energy management system and method. Background technique [0002] With the development of automobiles in the direction of intelligence, networking and electrification, it has become an effective means to solve the problems of energy saving and new energy vehicle control optimization with the help of Internet of Vehicles technology, which provides a new idea for it and helps to realize the Internet of Things Optimizing and improving the comprehensive performance of vehicles in the environment. [0003] Energy management algorithm is the core technology to ensure the fuel economy of hybrid electric vehicles, and researchers have done a lot of research on it. According to whether optimization theory is adopted, it can be divided into optimization-based energy management algorithm and rule-based control str...

AI Technical Summary

Problems solved by technology

[0006] In general, most of the current research on traditional energy management algorithms is theoretically optimized based on specific standard cycle conditions. Even if the vehicle’s historical operating condition data is used to predict the operating conditions, it is difficult to reflect the randomness and dynamics of the actual operating conditions, and the prediction stability is poor. , which cannot meet the requirements of fuel economy, real-time performance and adaptability to dynamic working conditions of the algorithm under the constraints of changing working conditions in the networked environment

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