Evidence map›Paper›PMID 36992021›Full record

ArticleSensors (Basel, Switzerland)2023

Study on Multi-Mode Switching Control Strategy of Active Suspension Based on Road Estimation.

Jianze Liu, Jiang Liu, Yang Li, Guangzheng Wang, Fazhan Yang

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Research on LPV-HScientific reports · 2025
    Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Jianze LiuInstitute of Mechanical and Automotive Engineering, Qingdao University of Technology, Qingdao 266520, China.ORCID 0000-0003-4621-9043
Jiang LiuInstitute of Mechanical and Automotive Engineering, Qingdao University of Technology, Qingdao 266520, China.
Yang LiInstitute of Mechanical and Automotive Engineering, Qingdao University of Technology, Qingdao 266520, China.
Guangzheng WangInstitute of Mechanical and Automotive Engineering, Qingdao University of Technology, Qingdao 266520, China.
Fazhan YangInstitute of Mechanical and Automotive Engineering, Qingdao University of Technology, Qingdao 266520, China.

Funding

Natural Science Foundation of Shandong Province No. ZR202111180079State Key Laboratory of Automotive Simulation and Control Open Foundation No. 20210226
6 · The paper itself

Abstract

In this paper, the least squares method is used to determine the vertical height of the road space domain. Based on the road estimation method, the active suspension control mode switching model is constructed, and the dynamic characteristics of the vehicle in comfort, safety, and integrated modes are analyzed. The vibration signal is collected by the sensor, and the parameters such as vehicle driving conditions are solved for in reverse. A control strategy for multiple mode switching under different road surfaces and speeds is constructed. At the same time, the particle swarm optimization algorithm (PSO) is used to optimize the weight coefficients of LQR control under different modes, and the dynamic performance of vehicle driving is comprehensively analyzed. The test and simulation results show that the road estimation results under different speeds in the same road section are very close to the results obtained by the detection ruler method, and the overall error is less than 2%. Compared with the active suspension controlled by passive and traditional LQR, the multi-mode switching strategy can achieve a better balance between driving comfort and handling safety and stability, and also improve the driving experience more intelligently and comprehensively.

Indexed as

mode switchingPSO_LQG controlroad estimationvehicle engineeringvibration test

Identifiers

PMID36992021
PMCPMC10059842

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.