Evidence map›Paper›PMID 38830917›Full record

ArticleScientific reports2024

Optimization of PID control parameters for marine dual-fuel engine using improved particle swarm algorithm.

Zhuo Hu, Weihao Guo, Kege Zhou, Lei Wang, Fu Wang, Jinliang Yuan

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

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3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

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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

6 authors.

Zhuo HuFaculty of Maritime and Transportation, Ningbo University, Ningbo, 315211, People's Republic of China.
Weihao GuoFaculty of Maritime and Transportation, Ningbo University, Ningbo, 315211, People's Republic of China.
Kege ZhouFaculty of Maritime and Transportation, Ningbo University, Ningbo, 315211, People's Republic of China.
Lei WangChina Coal Society, Beijing, 100013, People's Republic of China.
Fu WangFaculty of Maritime and Transportation, Ningbo University, Ningbo, 315211, People's Republic of China. wangfu@nbu.edu.cn.
Jinliang YuanFaculty of Maritime and Transportation, Ningbo University, Ningbo, 315211, People's Republic of China.

Funding

National Natural Science Foundation of China 52276010
6 · The paper itself

Abstract

This study presents a comprehensive investigation into the optimization of PID control parameters for marine dual-fuel engines using an improved particle swarm algorithm. Through the development of a Matlab/Simulink simulation model, the thermodynamic behavior of the engine and the functionality of its control system are analyzed. The PID control parameters for air-fuel ratio control and mode switching control systems are fine-tuned utilizing the improved particle swarm algorithm (PSO). Simulation results demonstrate that the proposed improved PID-PSO approach outperforms traditional PID and traditional PSO-PID control methods in terms of reduced overshoot, minimized steady-state error, faster response times, and improved stability across various operating conditions and response modes. In comparison to traditional PID and PSO-PID controllers, the improved PSO-PID controller reduces the response time by 0.47 s and 0.21 s, the maximum overshoot by 98.43% and 96.05%, and decreases the absolute errors by 87.42% and 90.55%, respectively, in air-fuel ratio control using the step response method. The study's findings offer valuable insights into enhancing the performance and efficiency of marine dual-fuel engines through advanced control strategies.

Indexed as

Air–fuel ratioDual-fuel engineFuel replacement ratioParticle swarm algorithmPID control

Identifiers

PMID38830917
PMCPMC11148095

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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.