Evidence map›Paper›PMID 24854061›Full record

ArticleSensors (Basel, Switzerland)2014

An optimal current observer for predictive current controlled buck DC-DC converters.

Run Min, Chen Chen, Xiaodong Zhang, Xuecheng Zou, Qiaoling Tong, Qiao Zhang

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2014. 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. 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

6 authors.

Run MinSchool of Optical and Electronic Information, Huazhong University of Science and Technology, Wuhan 430074, China. hustminrun@gmail.com.
Chen ChenSchool of Optical and Electronic Information, Huazhong University of Science and Technology, Wuhan 430074, China. chenchen_hust@163.com.
Xiaodong ZhangSchool of Optical and Electronic Information, Huazhong University of Science and Technology, Wuhan 430074, China. sanctum.zhang@gmail.com.
Xuecheng ZouSchool of Optical and Electronic Information, Huazhong University of Science and Technology, Wuhan 430074, China. estxczou@gmail.com.
Qiaoling TongSchool of Optical and Electronic Information, Huazhong University of Science and Technology, Wuhan 430074, China. tongqiaoling@hust.edu.cn.
Qiao ZhangSchool of Automation, Huazhong University of Science and Technology, Wuhan 430074, China. zhangqiao@263.net.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In digital current mode controlled DC-DC converters, conventional current sensors might not provide isolation at a minimized price, power loss and size. Therefore, a current observer which can be realized based on the digital circuit itself, is a possible substitute. However, the observed current may diverge due to the parasitic resistors and the forward conduction voltage of the diode. Moreover, the divergence of the observed current will cause steady state errors in the output voltage. In this paper, an optimal current observer is proposed. It achieves the highest observation accuracy by compensating for all the known parasitic parameters. By employing the optimal current observer-based predictive current controller, a buck converter is implemented. The converter has a convergently and accurately observed inductor current, and shows preferable transient response than the conventional voltage mode controlled converter. Besides, costs, power loss and size are minimized since the strategy requires no additional hardware for current sensing. The effectiveness of the proposed optimal current observer is demonstrated experimentally.

Identifiers

PMID24854061
PMCPMC4063073

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Registered trials

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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.