Energy switching control method and energy switching control system for hybrid electric vehicle in multiple operating modes

Abstract

Disclosed are an energy switching control method and an energy switching control system for a hybrid electric vehicle in multiple operating modes. The energy switching control method includes the steps: firstly, according to vehicle running environments and road conditions detected in real time by a vehicular GPS (global positioning system) and a sensor, and according to current running road condition information of the hybrid electric vehicle, determining the corresponding operating modes of the vehicle, wherein the operating modes specifically include an engine-driven operating mode, a motor-driven operating mode, an engine and motor hybrid driven operating mode and an energy feedback and regenerative brake operating mode; and then designing a multi-mode switching control rule for the driving modes in terms of the running road conditions, and designing corresponding controllers for the operating modes respectively. According to the running environments and the road conditions, the energy switching control method and the energy switching control system control the optimal vehicle driving modes so as to reduce emission of vehicle exhaust, save fuel oil consumption, accelerate development of environment-friendly vehicles and green vehicles and improve endurance of the hybrid electric vehicle.

Description

[0001] technical field [0002] The invention belongs to the field of energy management and control of a hybrid electric vehicle, in particular to an energy switching control method and system for a hybrid electric vehicle in multiple working modes. Background technique [0003] In recent years, with the global environmental and energy issues becoming more and more prominent, the development of new vehicles with low emissions and low fuel consumption has become the primary task of the development of the automotive industry today. Hybrid electric vehicle is a new type of clean energy vehicle developed to solve the energy crisis and vehicle emission problems. It combines the advantages of pure electric vehicles and traditional fuel vehicles. It not only has the characteristics of energy saving and environmental protection of pure electric vehicles, but also improves the fuel economy of the whole vehicle. and emission performance, and inherited the advantages of long continuous...

AI Technical Summary

Problems solved by technology

At present, only the logical threshold energy management strategy designed based on engineering experience has been applied in the actual commercial hybrid electric vehicle, but this method mainly relies on the existing experience to set the initial value of the parameters, and adjusts these parameters in combination with the "trial and error method". Although it has certain practicability, it cannot guarantee the best matching of the power system and cannot make the vehicle system achieve the maximum efficiency.

The global optimal energy management strategy can obtain the global optimal solution of control variables (such as engine / motor torque), but these methods require known driving conditions and are difficult to apply to real vehicle control

Instantaneously optimize the energy management strategy, which can achieve the minimum fuel consumption at each moment when the working conditions are unknown, but it requires a large number of floating-point operations, which is difficult to implement

In addition, although the intelligent control energy management strategy based on fuzzy logic has the advantages of strong robustness and good real-time performance, the establishment of its fuzzy controller mainly relies on experience and cannot obtain the global optimal

Since the hybrid vehicle energy management strategy problem is a typical nonlinear dynamic optimization problem with multiple variables (including both continuous variables and discrete variables), it is difficult to use a certain method to make a major breakthrough in theory, and there is still no way to solve it. The optimal solution applied to real vehicle control to break through the technical bottleneck of practical and high-performance energy management strategies

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