Parallel hybrid electric vehicle energy management method based on self-supervised learning

A hybrid vehicle and energy management technology, applied in hybrid vehicles, motor vehicles, control devices, etc., can solve problems such as lack of research, and achieve the effects of good maintenance, low fuel consumption, and guaranteed service life

Pending Publication Date: 2022-06-28
JIANGSU HAOFENG AUTO PARTS
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  • Description
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Problems solved by technology

At present, the energy management control strategy using reinforcement learning algorithm h

Method used

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  • Parallel hybrid electric vehicle energy management method based on self-supervised learning
  • Parallel hybrid electric vehicle energy management method based on self-supervised learning
  • Parallel hybrid electric vehicle energy management method based on self-supervised learning

Examples

Experimental program
Comparison scheme
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Example Embodiment

[0082] Embodiment 1 selects Prius parallel HEV as the research object, and its structure and working principle are as follows figure 1 shown. In the drive system of the parallel hybrid electric vehicle, the prime mover and the electric motor can jointly or independently provide torque to the vehicle drive train, and there is no generator. The vehicle parameters of the parallel hybrid electric vehicle are shown in Table 1:

[0083] Table 1 shows the vehicle parameters of the Prius parallel HEV

[0084]

[0085] S1: According to the vehicle parameters of the Prius parallel HEV and the vehicle structure principle, establish the vehicle longitudinal dynamics model, engine model, motor model, gearbox CVT model and battery model of the parallel vehicle.

[0086] When the vehicle is running, it will be affected by the resistance that hinders its movement. The resistance mainly includes rolling resistance, air resistance, slope resistance, and acceleration resistance. According ...

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Abstract

The invention relates to a parallel hybrid electric vehicle energy management method based on self-supervised learning, and belongs to the technical field of hybrid electric vehicle control. According to the method, a hierarchical reinforcement learning structure is provided by using a self-supervised learning method, so that the problem of sparse rewards is solved, different working conditions can be adapted while the fuel economy of the vehicle is improved, and optimized energy control of the HEV is realized. Compared with a traditional reinforcement learning algorithm, the management method has the advantages that the fuel economy is improved; the provided algorithm is close to the optimal fuel consumption curve, and when the rotating speed is increased, it can be guaranteed that the engine works in a low-fuel-consumption and high-power area as much as possible; the SOC value of the battery can be better maintained, the charging and discharging times are reduced, and the service life of the battery is ensured.

Description

technical field [0001] The invention relates to a parallel hybrid electric vehicle energy management method based on self-supervised learning, and belongs to the technical field of hybrid electric vehicle control. Background technique [0002] At present, with the rapid increase of automobile production, automobiles bring great convenience to people's daily travel and life, but also produce increasingly severe environmental and energy problems. Hybrid vehicles are a suitable solution for public transport due to their low energy consumption and long range. The purpose of the energy management control strategy is to coordinate the power distribution between the engine and the electric machine to maximize economy and maintain a stable state of charge (SOC). [0003] Energy management control strategies can generally be divided into rule-based, optimization-based and learning-based methods. A rule-based approach that is simple, reliable and adaptable. However, for different c...

Claims

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Application Information

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IPC IPC(8): B60W20/00B60W20/15B60W50/00
CPCB60W20/00B60W20/15B60W50/00B60W2050/0028
Inventor 齐春阳肖峰
Owner JIANGSU HAOFENG AUTO PARTS
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