Internet of vehicles based hierarchical energy management control method for hybrid vehicle

Abstract

The invention discloses an internet of vehicles based hierarchical energy management control method for a hybrid vehicle. An upper controller acquires a range of a target speed of the hybrid vehicle on the basis of traffic signal light timing and sets the target speed of the hybrid vehicle as an upper limit of the range of the target speed, and a fast model prediction algorithm is provided for predicating an optimal target speed sequence within a given time window. Compared with the prior art, the internet of vehicles based hierarchical energy management control method for the hybrid vehicle has the advantages that by predication of the optimal target speed of the hybrid vehicle on the basis of traffic signal light timing, stopping or collision of the hybrid vehicle at a red light can be effectively avoided; by acquisition of the optimal target speed sequence according to the fast model prediction algorithm, time cost of model prediction is reduced on the premise that predicated data precision and fuel economy of the hybrid vehicle are guaranteed, and program execution efficiency is effectively improved.

Description

technical field [0001] The invention relates to an energy management control method for a hybrid electric vehicle, in particular to a hierarchical energy management control method for a hybrid electric vehicle based on the Internet of Vehicles. Background technique [0002] The energy management control method of hybrid electric vehicles directly affects the power performance, economy, comfort and emission of the whole vehicle, which is the focus and difficulty of research in the field of hybrid electric vehicles. At present, the rule-based control method has been applied industrially. However, the rule-based control method relies on expert experience and does not have good adaptability to working conditions. Therefore, scholars focus on the optimization-based control method. [0003] Optimization-based control methods mainly include global optimization and instantaneous optimization. In the global optimization algorithm, dynamic programming (dynamic programming, DP), quadr...

AI Technical Summary

Problems solved by technology

However, compared with the computing power of the on-board microcontroller, these algorithms still cannot achieve real-time control

The current hybrid vehicle energy management research object is only one vehicle, that is, the energy management optimization algorithm can only ensure the optimal economy of a single vehicle, and there is no relevant research on energy management optimization of multiple hybrid vehicles in the traffic system report

In addition, the current control algorithm for the energy management and optimization of a single hybrid electric vehicle does not consider the influence of traffic signals and the interaction between vehicles. There is a certain gap in the optimal solution

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