Automobile prediction cruise parameter self-tuning control system based on fusion of driving mode information

A parameter self-tuning and driving mode technology, applied in the direction of control devices, etc., can solve the problems of not applying the cruise control system and not involving the weight parameter self-tuning, so as to reduce manpower, improve fuel economy, and reduce fuel consumption.

Active Publication Date: 2021-09-17
JILIN UNIV
View PDF14 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, this method does not involve the self-tuning of weight parameters in multi-objective optimization, and this method has not been applied to the cruise control system of the vehicle

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
  • Automobile prediction cruise parameter self-tuning control system based on fusion of driving mode information
  • Automobile prediction cruise parameter self-tuning control system based on fusion of driving mode information
  • Automobile prediction cruise parameter self-tuning control system based on fusion of driving mode information

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0055] The present invention considers the cruising and car-following scene. The system first uses a clustering algorithm to identify the driving mode of the preceding vehicle based on rich multi-source heterogeneous network information; The Yeasian optimization method automatically tunes the weight parameters in the multi-objective optimization function, and obtains the optimal weight parameters that minimize the energy consumption of the vehicle in a certain driving mode of the preceding vehicle. Finally, based on the current driving mode identification of the preceding vehicle Results The weight parameters adjusted were used to adjust the weight parameters of the multi-objective optimization function in the PCC system of the vehicle, so as to achieve the goal of further improving the fuel economy of the vehicle when the vehicle was cruising and following the vehicle.

[0056] The present invention is achieved through the following technical solutions:

[0057] 1. Informatio...

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 discloses a networked automobile prediction cruise parameter self-tuning control system based on fusion of driving mode recognition information, and belongs to the field of intelligent networked automobile energy-saving control. The invention aims to provide an automobile prediction cruise parameter self-tuning control system based on the fusion of the driving mode information, which identifies the automobile driving mode by means of data mining, improves the fuel economy of the automobile, and greatly reduces the multi-objective optimization control right tuning workload at the same time. The system comprises the steps of information collection, preceding vehicle driving mode clustering and recognition, prediction cruise controller design and parameter tuning design based on a Bayesian optimization method. According to the method, a group of optimal weight parameters can be quickly and accurately solved, so that a large amount of trial and error required when the weight is manually selected is effectively avoided. The manpower for adjusting the weight parameters is greatly reduced, and the driving comfort and the tracking performance are improved to a certain extent.

Description

technical field [0001] The invention belongs to the field of energy-saving control of intelligent networked vehicles. Background technique [0002] The cruise control system can replace the driver to complete the longitudinal follow-up driving, and has been widely used in the car assisted driving system. At this stage, with the development of mobile internet, big data and other technologies, it is possible for intelligent networked vehicles to obtain the surrounding traffic information in real time. Using this information, with the empowerment of advanced control methods, optimize the cruise following strategy, which can further improve the Fuel economy, comfort and safety of automobiles. [0003] Patent CN105857309A discloses a vehicle adaptive cruise control (Adaptive Cruise Control, ACC) method considering multiple objectives. The method adopts a layered control strategy, obtains the desired longitudinal acceleration through the upper layer control, and then realizes th...

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): B60W30/14B60W30/16B60W50/00
CPCB60W30/14B60W30/16B60W50/00B60W2050/0034B60W2520/10B60W2520/105B60W2554/802
Inventor 宫洵王昱昊胡云峰林佳眉曲婷王宁李勇陈虹
Owner JILIN UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap