Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Hybrid electric vehicle reinforcement learning energy management control method

A technology of hybrid electric vehicles and enhanced learning, which is applied in hybrid electric vehicles, motor vehicles, transportation and packaging, etc., can solve the problems of small battery capacity decline and low fuel consumption, and achieve the optimization of vehicle economy, simplification of calculations, The effect of battery capacity decline optimization

Active Publication Date: 2019-09-20
FUZHOU UNIV
View PDF7 Cites 32 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the goals of minimal battery capacity degradation and lowest fuel consumption are in conflict

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Hybrid electric vehicle reinforcement learning energy management control method
  • Hybrid electric vehicle reinforcement learning energy management control method
  • Hybrid electric vehicle reinforcement learning energy management control method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0052] The technical solution of the present invention will be specifically described below in conjunction with the accompanying drawings.

[0053] like figure 1 As shown, the present invention provides a hybrid electric vehicle enhanced learning energy management control method that takes into account battery life and economy, and uses the equivalent fuel consumption minimum strategy and enhanced learning algorithm to optimize the control of battery degradation and vehicle equivalent fuel consumption. In order to achieve the best economic performance of the vehicle, the specific steps are as follows:

[0054] Step S1, collecting vehicle status and battery status data;

[0055] The vehicle state data includes: vehicle speed, required power, engine speed and motor speed, and the battery state data includes: battery current, voltage, temperature and SOC.

[0056] Step S2, establishing a hybrid vehicle ICE (Internal Combustion Engine) model, an EM (Electric Motor) model and a t...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention relates to a hybrid electric vehicle reinforcement learning energy management control method. According to the hybrid electric vehicle reinforcement learning energy management control method, by combining an equivalent consumption minimization strategy and a reinforcement learning algorithm and optimizing fuel consumption and battery capacity degradation, a target of optimal use cost of a whole hybrid electric vehicle is achieved. The hybrid electric vehicle reinforcement learning energy management control method comprises the following steps of 1) collecting vehicle state and battery state data; 2) establishing an ICE (Internal Combustion Engine) model, an EM (Electric Motor) model and a transmission system model of the hybrid electric vehicle, a battery internal resistance model and a battery degradation model; and 3) combining the equivalent consumption minimization strategy and the reinforcement learning algorithm, establishing a hybrid electric vehicle energy management strategy, calculating a multi-target optimization problem, and generating a control signal according to a calculation result to distribute engine power and motor power.

Description

technical field [0001] The invention relates to the field of hybrid electric vehicle energy management, in particular to a hybrid electric vehicle enhanced learning energy management control method. Background technique [0002] Today, gasoline, diesel and other fuels used by traditional fuel vehicles are facing a crisis of depletion. At the same time, vehicle exhaust emissions are also causing more and more serious pollution to the environment. New energy vehicles have become an inevitable trend in the development of vehicles. As a form of new energy vehicles, pure electric vehicles still have many problems that have not been effectively resolved in terms of cruising range, battery life, and cost of use. As a form of transition from traditional fuel vehicles to pure electric vehicles, hybrid electric vehicles (Hybrid Electric Vehicles, HEVs) have become the focus of current research in the automotive field. [0003] The power system of a hybrid electric vehicle is composed...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Applications(China)
IPC IPC(8): B60W20/13B60W20/15
CPCB60W20/13B60W20/15B60W2510/0638B60W2510/081B60W2510/242B60W2510/246
Inventor 林歆悠王召瑞伍家鋆周斌豪张光吉
Owner FUZHOU UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products