PEMFC Simulation & Modeling Patent Landscape 2026
The PEMFC simulation and modeling space is in a Growth stage, with a 146% expansion in recent filings concentrated overwhelmingly among Chinese universities and a handful of global industrials. Nanjing University of Aeronautics and Astronautics leads the applicant ranking, while multi-physics coupling and water-management modeling dominate the most-cited prior art.
Chinese universities lead a fragmented but rapidly growing field
Nanjing University of Aeronautics and Astronautics holds the top position with 10 patent records, followed by Xi’an Jiaotong University with 8 and Tianjin University and Dassault Systèmes Americas Corp each with 7. The top five filers together account for 22% of the combined output of the hundred largest filers, indicating a field that is active but not yet dominated by any single incumbent.
The tier gap between the leader (10 patent records) and the mid-pack (3–4 records each) is narrow, which means the current ranking is contestable. No single applicant has established a commanding share that would deter entry from well-resourced challengers.
| # | Applicant | Patent records | Share |
|---|---|---|---|
| 1 | NANJING UNIV OF AERONAUTICS & ASTRONAUTICS | 10 | |
| 2 | Xi’an Jiaotong University | 8 | |
| 3 | Tianjin University | 7 | |
| 4 | Dassault Systèmes Americas Corp | 7 | |
| 5 | KOREA ADVANCED INST OF SCI & TECH | 5 | |
| 6 | Jilin University | 4 | |
| 7 | Tsinghua University | 4 | |
| 8 | University of Leeds | 4 | |
| 9 | Southwest Jiaotong University | 3 | |
| 10 | Wuhan University of Technology | 3 |
| # | Applicant | Patent records | Share |
|---|---|---|---|
| 11 | Hunan Institute of Science and Technology | 3 | |
| 12 | Kusn Fuersai Energy | 3 | |
| 13 | North China Electric Power University | 3 | |
| 14 | KUNMING UNIV OF SCI & TECH | 3 | |
| 15 | GM Global Technology Operations LLC | 3 | |
| 16 | Ford Global Technologies LLC | 3 | |
| 17 | Shanghai Hydrogen Propulsion Technology Co., Ltd. | 2 | |
| 18 | UNIV OF SCI & TECH BEIJING | 2 | |
| 19 | Thomas J. Pavlik | 2 | |
| 20 | UNIV OF SHANGHAI FOR SCI & TECH | 2 |
The presence of Dassault Systèmes Americas Corp — a commercial simulation software vendor — among the top four signals that simulation-tool IP is being filed alongside fundamental cell-physics modeling, creating distinct competitive sub-tracks within the same landscape.
Filings from approximately 2024 onward are subject to standard publication lag and are likely under-counted; interpret recent-year totals as a floor rather than a ceiling. Longer-window growth, applicant concentration, and technology-route coverage are therefore more reliable signals than the latest-year bar alone.
Filings rising sharply; fuel-cell physics and computational methods co-dominate
The annual filing trend reveals a clear growth arc from 2019 onward, while the technology composition chart shows that PEMFC-specific classification (H01M) and general computational methods (G06F) together account for the large majority of activity — with AI and computational chemistry appearing as smaller but meaningful adjacent branches.
Annual filing trend
Activity was negligible through 2018, began climbing from 2019, and accelerated sharply from 2022 through 2024, consistent with the 146% recent-period growth figure. The 2025–2026 bars are suppressed by publication lag and should not be read as a slowdown.
↗ Hover for values · click a bar to ask EurekaTechnology composition
H01M (fuel cells) and G06F (digital data processing / simulation software) are the two dominant branches, reflecting the hybrid nature of the field — physical cell modeling combined with computational implementation. G06N (AI models) and G16C (computational chemistry) appear at materially lower counts, marking them as adjacent rather than core to current filings.
↗ 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.
Computer simulation methodology to analyze mass, m…
A method analyzes physical transport in a proton exchange membrane fuel cell (PEMFC) having three adjacent layers L<sub>1</sub>, L<sub>2</sub>, L<sub>3</sub>, each with a distinct porous structure. A first small scale multiphase simulation S<sub>1 </sub>of a first portion of the L<sub>1</sub>/L<sub>2 </sub>interface is used to characterize the… (excerpt from the patent abstract)
| # | Patent | Citations |
|---|---|---|
| 1 | 质子交换膜燃料电池内部水分布预测方法 | 46 |
| 2 | 基于多物理场的质子交换膜燃料电池水淹故障诊断方法 | 36 |
| 3 | 一种改进粒子群优化模糊PID燃料电池温度控制方法 | 31 |
| 4 | Proton exchange membrane fuel cell | 30 |
| 5 | Fuel cell flowfield design for improved water mana… | 28 |
| 6 | 一种质子交换膜燃料电池用膜加湿器控制方法 | 25 |
| 7 | 一种质子交换膜燃料电池多物理场耦合模拟方法 | 23 |
| 8 | PEMFC双极板流道截面的优化方法及三维质子交换膜燃料电池 | 21 |
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.
What the competitive structure means for R&D investment
Three structural signals stand out: the field is in active growth, the ranking is contestable, and geographic concentration in. China creates exposure and opportunity for non-Chinese entrants.
Growth stage — annual filings still rising
The lifecycle evidence designates this field as Growth, with annual filings still rising and a 146% expansion over the recent measurement window. The technology base is maturing enough that multi-physics coupling and water-management methods are well-cited, but early-mover advantages are still available in adjacent computational branches. Teams entering now can still shape claim boundaries rather than designing around established walls.
Growth stageFragmented top tier — low barrier to ranking entry
The top five filers hold only 22% of the hundred largest filers’ combined output, and the leader holds just 10 patent records. This fragmentation means there is no entrenched gatekeeper whose portfolio would require extensive freedom-to-operate work for a newcomer. However, the narrow gaps also mean that a focused two-to-three-year filing program could move a new entrant into the top five.
Low concentrationSparse co-filing activity observed between Chinese institutions
Three co-applicant pairs are recorded in the evidence: Tsinghua University with the State Grid Qinghai Electric Power Company’s Economic and Technical Research Institute (1 joint filing), Tsinghua University with State Grid Qinghai Electric Power Company (1 joint filing), and Jilin University with Hua Ao Anxin Technology Service Group (1 joint filing). The low collaboration count relative to total filings suggests that most participants are filing independently, leaving ecosystem partnership strategies relatively open.
Early ecosystemChina overwhelmingly dominant; US and PCT filings thin
China accounts for 100 of the patent records, the United States for 25, India and WIPO (PCT) for 6 each, with Germany and Europe (EPO) at 3 each. The high China-to-PCT ratio suggests that much of the Chinese academic output is not being internationalized, which limits its enforceability outside China but also limits the prior-art barrier it poses to filings in Europe or North America. Non-Chinese applicants filing PCT or EPO routes face comparatively less prior art from the dominant filers.
China-centricGo beyond the landscape: Eureka’s TRIZ Solution agent breaks down an R&D problem and returns patented concept solutions, each with a technical approach and cited patent & literature evidence.
| Applicant | Collaborator | Co-filings |
|---|---|---|
| Tsinghua University | State Grid Qinghai Electric Power Company Economic and Technical Research Institute | 1 |
| Tsinghua University | State Grid Qinghai Electric Power Company | 1 |
| Jilin University | Hua Ao Anxin Technology Service Group Co., Ltd. | 1 |
Co-filing pairs, ranked by the number of jointly-filed patent families.
Academic institutions lead; one commercial simulation vendor in the top four
The ranking is topped by Chinese universities pursuing multi-physics and computational simulation of PEMFC systems, with Dassault Systèmes Americas Corp as the only commercial software entity in the top tier and KAIST as the leading non-Chinese academic presence.
Nanjing University of Aeronautics and Astronautics
The top-ranked applicant with 10 patent records, concentrating its filings across H01M 8 (fuel cell systems) and G06F 30 (simulation and digital computation), indicating a strong focus on coupled physical and computational modeling of PEMFC performance. Momentum is flagged as a new entrant in the recent period, with 7 of its records filed in the most recent window, showing an accelerating rather than established trajectory.
families: 10Dassault Systèmes Americas Corp
The sole major commercial software vendor in the top four, with 7 patent records split across H01M 8 and G06F 30, reflecting integration of PEMFC simulation within its broader simulation platform portfolio. Momentum is also flagged as a new entrant with 6 records in the recent period, suggesting a deliberate strategic push into fuel-cell simulation IP rather than a legacy position.
families: 7| Applicant | Recent (3 yrs) | Trend |
|---|---|---|
| Nanjing University of Aeronautics and Astronautics | 7 | ▲ new entrant |
| Xi’an Jiaotong University | 1 | ▲ new entrant |
| Tianjin University | 2 | ▲ new entrant |
| Dassault Systèmes Americas Corp | 6 | ▲ new entrant |
| Tsinghua University | 2 | ▲ new entrant |
| Jilin University | 2 | ▲ new entrant |
| Southwest Jiaotong University | 1 | ▲ new entrant |
Under-served branches adjacent to the PEMFC simulation core
Several IPC branches appear at low counts relative to the dominant H01M and G06F classes; these represent areas of relative sparsity that may merit monitoring, subject to technical feasibility and strategic fit.
G06N · AI-driven PEMFC modeling
G06N (computing based on AI models) appears in only 13 patent records — about 5% of the hundred largest filers’ combined branch coverage — despite machine-learning surrogate models being an active research topic for accelerating multi-physics simulations. The sparse IP footprint means that applicants pursuing physics-informed neural networks or reinforcement-learning-based control for PEMFC could file in a relatively uncrowded branch. Entry would require demonstrated accuracy trade-offs versus first-principles models, and patent claims would need to distinguish over general ML methods.
Search this in Eureka →G16C · Computational chemistry for membrane and catalyst modeling
G16C (computational chemistry and cheminformatics) accounts for only 9 patent records, representing roughly 3% of the branch coverage within the top-100 filers’ output, despite membrane degradation and electrocatalyst design being critical PEMFC bottlenecks addressable via molecular simulation. The low count suggests that atomistic or DFT-level modeling approaches for PEMFC materials are not yet being captured in significant patent filings, potentially because this work is published as academic literature rather than patented. Applicants with novel computational chemistry workflows tied to proprietary material candidates could find meaningful white space here.
Search this in Eureka →How leading applicants differ by technology route
Route coverage across the main technology branches in the current evidence set.
| Player | H01M 8 · Batteries, cells & fuel cells | G06F 30 · Electric digital data processing | G06F 119 · Electric digital data processing | G06F 113 · Electric digital data processing | G06F 111 · Electric digital data processing |
|---|---|---|---|---|---|
| Nanjing University of Aeronautics and Astronautics | Strong · 8 | Strong · 7 | Strong · 5 | Emerging · 1 | Moderate · 3 |
| Xi’an Jiaotong University | Strong · 6 | Strong · 7 | Strong · 4 | Strong · 4 | Moderate · 2 |
| Dassault Systèmes Americas Corp | Strong · 6 | Strong · 5 | Moderate · 2 | Absent | Absent |
| Tianjin University | Strong · 5 | Strong · 4 | Strong · 3 | Absent | Absent |
| Jilin University | Absent | Strong · 4 | Moderate · 2 | Strong · 3 | Moderate · 1 |
| Tsinghua University | Strong · 3 | Absent | Strong · 2 | Strong · 2 | Absent |
| University of Shanghai for Science and Technology | Absent | Strong · 2 | Strong · 2 | Moderate · 1 | Moderate · 1 |
Frequently asked questions
The corpus in scope contains 122 patent families. This represents activity captured across all major filing offices and reflects a 146% growth rate in the recent measurement window.
Nanjing University of Aeronautics and Astronautics leads with 10 patent records, followed by Xi’an Jiaotong University with 8, and Tianjin University and Dassault Systèmes Americas Corp each with 7.
The field is in a Growth stage. Annual filings are still rising, supported by a 146% recent-period expansion. The most recent one to two years of data are under-counted due to publication lag, so even the current figures likely understate true activity.
China accounts for 100 patent records — by far the largest jurisdiction — followed by the United States with 25, and India and WIPO (PCT) with 6 each. Germany and Europe (EPO) each account for 3 records.
The most-cited work addresses internal water distribution prediction in PEMFCs (46 citations), multi-physics-field water flooding fault diagnosis (36 citations), fuzzy PID temperature control via particle swarm optimization (31 citations), and a general PEMFC patent with 30 citations. Flow-field design for water management also appears prominently with 28 citations.
The sparsest adjacent branches are G06N (AI and machine-learning models, 13 patent records) and G16C (computational chemistry, 9 patent records). Both are materially under-represented relative to the dominant H01M and G06F classes, and both address technically relevant problems — surrogate modeling for speed and atomistic simulation for materials design — that are not yet heavily patented in this corpus.
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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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