VRFB Sensor Integration Patent Snapshot 2026
The patent corpus for VRFB sensor integration is nascent, comprising just 2 patent families concentrated entirely within China and dominated by no single player, with five applicants each holding one patent record. Activity is sparse and episodic, signalling that this sub-field remains largely unpenetrated by formal IP strategy.
Five applicants share an embryonic, fully fragmented field
The VRFB sensor integration corpus is exceptionally small. Five applicants — Tianjin Di’ai Information Technology Co., Wuhan University of Technology, Wuhan NARI (State Grid Electric Power Research Institute), Anhui Conch Ronghua Energy Storage Technology Co., and the Electric Power Research Institute of State Grid Shanxi Electric Power — each hold one patent record, placing them in a perfectly flat tie at the top of the ranking.
The top five filers collectively account for 100% of the ranked applicants visible in this query’ combined total, a figure that is analytically trivial here because the corpus is too small for tier gaps to be meaningful. There is no visible incumbent and no clear second tier.
| # | Applicant | Patent records | Share |
|---|---|---|---|
| 1 | Tianjin Di’ai Information Technology Co. Ltd | 1 | |
| 2 | Wuhan University of Technology | 1 | |
| 3 | Wuhan NARI Co. Ltd (State Grid Electric Power Research Institute) | 1 | |
| 4 | Anhui Conch Ronghua Energy Storage Technology Co. Ltd | 1 | |
| 5 | Electric Power Research Institute of State Grid Shanxi Electric Power Co. | 1 |
The flat ranking implies that no applicant has yet committed to a sustained IP-building programme in this sub-field. Any organisation that files even a modest portfolio over the next two to three years would immediately become the de facto leader.
Given the corpus size, recent-period counts should be treated with particular caution: publication lag of 18–24 months means filings from late 2024 onward are almost certainly under-represented in these figures. Longer-window growth, applicant concentration, and technology-route coverage are therefore more reliable signals than the latest-year bar alone.
Isolated filings in 2023 and 2025 define the entire trend; all activity sits in H01M
The annual filing trend and technology composition charts together reveal a field that has produced only scattered disclosures and has not yet developed a diversified technology branch structure.
Annual filing trend
Recorded activity shows a single filing in 2023 and one in 2025, with zero in all other years from 2017 to 2026. This is not a trend in any statistical sense — it reflects two isolated disclosures. The 2025 figure and any 2024–2026 activity should be treated as likely under-counted due to standard publication lag.
↗ Hover for values · click a bar to ask EurekaTechnology composition
All four patent records (across both families and their jurisdictional equivalents) map to H01M — Batteries, Cells & Fuel Cells. There is no secondary IPC class represented in the corpus, confirming that sensor-specific classification codes (e.g. measurement, control systems) have not yet been applied or that filings have been written primarily around the electrochemical system rather than the sensing sub-system.
↗ Hover for values · click a bar to ask EurekaHighly cited patent families surfaced by the query
Citation-heavy patent families returned by the query. Use this section as citation context, not as a curated list of the most topic-specific patents.
一种基于SVM的全钒液流电池泵故障检测方法
本发明涉及一种基于SVM的全钒液流电池泵故障检测方法，适用于电网储能系统，该方法不需要任何流量传感器，可对全钒液流电池泵的正极泵故障、负极泵故障及双侧泵故障进行分类。从电池状态曲线中提取特征参数，对支持向量机的参数进行了优化，最后通过支持向量机训练得到故障预测结果，实现对全钒液流电池泵的正极泵故障、负极泵故障及双侧泵故障进行故障分类。采用支持向量机算法检测全钒液流电池水泵在实际运行中的运行状态，并利用交叉验证算法优化支持向量机中的参数，能够很好地解决全钒液流电池泵故障检测的技术问题。 (excerpt from the patent abstract)
| # | Patent | Citations |
|---|---|---|
| 1 | 全钒液流电池储能系统 | 11 |
| 2 | 一种基于SVM的全钒液流电池泵故障检测方法 | 5 |
Ranked by total forward citations. Citation counts favour older and broadly cited patent families, and broad or adjacent patents may appear when they match the search scope. Treat this section as citation context, not as a curated list of the most topic-specific patents. Some patent titles may be shown in their original, non-English language where an accurate translation could not be guaranteed.
Assignee snapshot from the current evidence set
The applicants below are visible in this query result. Because the evidence set is relatively small, read this section as a directional snapshot rather than a full competitive ranking.
Tianjin Di’ai Information Technology Co.
Tianjin Di’ai Information Technology Co. holds 1 patent record focused on H01M 8 (fuel cells and flow batteries). No momentum trend is recorded in the evidence for this applicant, and their single filing places them in a five-way tie at the top of the ranking. As a specialised information-technology firm, their presence suggests a software or monitoring-system angle on VRFB sensor integration.
patent records: 1Wuhan University of Technology
Wuhan University of Technology also holds 1 patent record in H01M 8, but is distinguished from the other four applicants by its momentum classification: it is marked as a new entrant in the most recent period. This signals a fresh academic interest in the sub-field and could foreshadow additional filings as research programmes mature.
patent records: 1Frequently asked questions
The corpus contains 2 patent families in scope. This is a very small corpus, and filings from the most recent 18–24 months may not yet have published and are therefore under-represented.
Five applicants each hold one patent record: Tianjin Di’ai Information Technology Co., Wuhan University of Technology, Wuhan NARI (State Grid Electric Power Research Institute), Anhui Conch Ronghua Energy Storage Technology Co., and the Electric Power Research Institute of State Grid Shanxi Electric Power. No single applicant leads.
All four patent records on file are in China. No PCT, EPO, USPTO, or other jurisdictional filings are recorded in the evidence.
All four patent records map to H01M — Batteries, Cells and Fuel Cells. No secondary IPC class (such as G01 for measurement or G05 for control) appears in the corpus.
One co-filing relationship is recorded: Wuhan NARI (State Grid Electric Power Research Institute, Wuhan) and the Electric Power Research Institute of State Grid Shanxi Electric Power jointly filed one patent record. No other cross-organisation collaborations are detected.
Only two isolated filings are recorded — one in 2023 and one in 2025 — with zero activity in all other years from 2017 to 2026. The corpus is too small to support a reliable trend characterisation. The lifecycle stage is not formally assigned in the evidence, but the pattern is consistent with a nascent, pre-commercial sub-field.
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Disclaimer. This page is generated from Patsnap Eureka data drawn from a limited snapshot of global patent and scientific-literature records, and is provided for general information and reference only.
Patent data carries inherent limitations: recent filings (typically the most recent 18–24 months) are under-counted due to standard publication lag; counts may be reported at either a patent-family or a patent-record basis and are not always directly comparable; classification, applicant-name, and citation data may contain errors, duplicates, or omissions; and the underlying search query defines and constrains the scope shown. As a result, the analysis may be incomplete or inaccurate and may not reflect the full technology landscape.
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