How good are the Tesla patents? Who might want a free license?

Tesla Motors founder Elon Musk recently announced that “all of our patents belong to you’, for reasons described below: 

At Tesla, however, we felt compelled to create patents out of concern that the big car companies would copy our technology and then use their massive manufacturing, sales and marketing power to overwhelm Tesla. We couldn’t have been more wrong. The unfortunate reality is the opposite: electric car programs (or programs for any vehicle that doesn’t burn hydrocarbons) at the major manufacturers are small to non-existent, constituting an average of far less than 1% of their total vehicle sales.

At best, the large automakers are producing electric cars with limited range in limited volume. Some produce no zero emission cars at all.

Given that annual new vehicle production is approaching 100 million per year and the global fleet is approximately 2 billion cars, it is impossible for Tesla to build electric cars fast enough to address the carbon crisis. By the same token, it means the market is enormous. Our true competition is not the small trickle of non-Tesla electric cars being produced, but rather the enormous flood of gasoline cars pouring out of the world’s factories every day.

We believe that Tesla, other companies making electric cars, and the world would all benefit from a common, rapidly-evolving technology platform. 

Some others have claimed that Tesla are acting for the less pure motive of trying to create a technology standard that they will still have some a commercial stake in, or that they really are more interested in selling batteries (including to other car companies) than cars. Here at Ambercite we might leave the analysis of Tesla’s strategy to McKinseys, but we are interested as patent analysts in these more simple questions:

  • How good are the Tesla patents?
  • Who is filing patents that cite these patents, i.e. might most appreciate a free licence to them?

To answer, we can use the Portfolio Benchmarking report we have recently developed. A search for patents owned by Tesla Motors in Espacenet uncovered 196 unique patents (after Espacenet had removed duplicates). We ran these numbers through the our analysis process, and 190 of these patents were recognised by our system (the other 6 had just been published not yet been processed by our data analytics engine). Where patents were listed as being filed by an individual, we looked up the most likely corporate owner of these patents.

When were the patents filed?

The first Tesla patent was only filed in 2007, and filing activity has built up since then, as shown in the figure below. The dip in 2013 might be due to the 18 month gap between the filing of new patents and their publication – and should be disregarded at this point in time.



What were their best patents?

Ambercite has recently developed a Portfolio Benchmarking report for reviewing a portfolio of reports. 

Within these portfolio reports, AmberScore has been developed to predict what may be the most important patents, based on citation connections. Only 7 Tesla patents had AmberScore values greater than 1, which is the average for US patents less than 20 years old. At this point in time, there is little evidence that the Tesla patents are going to have a big impact in their field, with the possible exception of US7698078, which covers a method for remote monitoring of the battery in an electric vehicle. This has has both a very interesting range of forward citing companies, and very broad claims:

1. A method of communicating with an electric vehicle, said method including the steps of:

  • installing a communication device in the electric vehicle;
  • establishing a connection from the vehicle to a network;
  • communicating with a user interface via said network; and
  • controlling and monitoring a battery in the electric vehicle via a device remote from the electric vehicle.

These seven highest scoring Tesla patents are listed below:

Patent number (filing date)

Patent title

AmberScore (Local dominance)

Forward citation count

# forward citations filed in last 5 years

Backward citation count

Most common owner of forward citation patents

US7698078 (2007-07-18)

Electric vehicle communication interface






IBM (3), Daimler [Benz] (2), GM (2) Porsche(1), Siemens (1)

US7890218  (2007-07-18)

Centralized multi-zone cooling for increased battery efficiency






Tesla (3), Ferrari (2), Porsche (1) Commscope(1), GM(1)

US8696051   (2012-12-06)

System for absorbing and distributing side impact energy utilizing a side sill assembly with a collapsible sill insert






Renault (1)

US8720968  (2012-05-29)

Charge port door with electromagnetic latching assembly






Tesla (1), Nissan (1), Toyota (1)

US8402776  (2012-03-23)

Thermal management system with dual mode coolant loops






Hyundai (1)

US8664907  (2011-01-31)

Fast switching for power inverter






Tesla (2), GE (1)

US8054038  (2009-01-29)

System for optimizing battery pack cut-off voltage






Cisco (3), VW (2), Denso (1), Yazaki (1)


US80544038 looks like it might become a more influential patent in future years, as it is already attracting a good range of forward citations.

The remainder of the Tesla patents can be reviewed by clicking on the image below:



Who is filing the most forward citations?

Besides Tesla, only General Motors has filed a high number of patents that cite the Tesla patents, as shown below:




This is only a partial list of car or well known companies with forward citaitons. The full list includes:

  • Toyota
  • Peugeot Citroen
  • Renault
  • Hyundai
  • Samsung
  • Suzuki
  • Ferrari
  • IBM
  • LG
  • Lear Corporation
  • Ford
  • Polaris
  • Nissan
  • Panasonic
  • Honda

In other words, a lot of companies appear to be interested in electric vehicles or associated technologies



This short review of the Tesla patent has shown that

  • They are all quite recent
  • With the exception of the very broad US7698078, these patents are yet to have a significant impact on the patent literature – but they are all comparitively recent.
  • General Motors is the company who may benefit the most from a free license to these patents. But many other car companie are filing similar patents/


PS – how does this compare to other patent portfolios?

For contrast, the Tesla patent portfolio can be compared to other reports we have published for:

And your own patent porfolio? Please contact us for details of how we can benchmark your own portfolio against these other published results.


Follow up – how valid is Tesla’s leading patent, US7698078?

In a follow-up to this blog, we conduct a search for uncited but relevant prior art – and find some patents at least as good if not better as anything found by the examiner. Click here for further details.

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Who might be directly affected by the US ‘Alice’ ruling? A case study of patent similarity analysis


The US Supreme Court has famously just invalidated US5970479, filed by Alice Corporation for Methods and apparatus relating to the formulation and trading of risk management contracts, or a method of managing counter party risk during exchange of contract. The reason for this judgement can be summarised by the following extract from the judgement:

An instruction to apply the abstract idea of intermediated settlement using some unspecified, generic computer is not “enough” to transform the abstract idea into a patent-eligible invention

The judgement has been reviewed by many others, with a common theme in the commentary being that the judgement failed to clearly define what an abstract idea is. Another theme is that this ruling is thought to have left the door open for software inventions, although of note the word ‘software’ was not mentioned once in the entire judgement.

Here are Ambercite we might leave the detailed intepretation of US Supreme Court judgments to others better qualified. But it is worth asking the question – who might be most affected by this judgement?



One way of answering this question is by asking – which patents are most similar to the Alice judgement?

Ambercite believes that similarity can be assessed to a good degree of reliability by considering overlapping citation between patents. This is the principle behind the similarity filter found in our Amberscope web app – a case study for this similarity filter is found here. Similar principles can even be used to find similar patents not directly connected to the patent in question, and this is the principle behind the Automated Patent Searches now available from Amberscope

One of these searches. a Similar Patent Finder, lists up to 50 earlier and 50 later patents similar to your patent of interest, including similar patents not directly connected to your patent of interest.

At a case study of this automated search, we have looked for similar patents to the Alice patent. These results of the Automated Search can be downloaded here, or by clicking on the image below:



So what does a ‘Similar Patent Finder’ patent search tell us about which companies might be directly affected by the Alice judgement?

1) Altogether this patent has 287 forward citations, with 67 of these filed in the last 5 years. There has been a lot of follow up activity in this area.

2) The most common owners of forward citation patents include

3a) The owners of the 20 most similar backward citations include

The most predicted to be similar patent was US4903201, for an Automated futures trading exchange. While now expired, asking whether claim this would fall foul of the Alice judgement could be a good question for law students. While claim 1 does refer to the use of the computer in a general way, claim 1 also refers to criteria for system for detecting illegal trade practices or patterns.

All of these patents, like many others listed in this search resuults, all appear to be related to securties trading.

3b) The owners of the most similar forward citations include

The most predicted to be similar patent not owned by Alice Corporation was US632121, for Financial products having a demand-based, adjustable return, and trading. Claim 1 of this patent covers a method for conducting demand-based trading – whether this would be regarded as an ‘abstract idea’ similar to ‘intermediated settlement’ in the light of the Alice judgement could be a very interesting question.

4a) The owners of the potentially similar earlier patents, not cited by the examiner or applicant, include some larger well known companies as well as some smaller companies.

4b) The owners of the potentially later earlier patents, not cited by the examiner or applicant, include, besides some earlier mentioned companies:


Of course, we would all recognise that whether the patents listed in this search are actually at risk of invalidation in the light of the Alice judgement is a complex decision depending on the details of the claims for these patents and other contributing factors. 


Other parties that might be affected

Almost all of the patents listed are in the area of securties trading or related technlogies. This patent has been assigned a CPC patent code of G06Q 40/02, G06Q 40/04, G06Q 40/08  all which relate to data processing in banking or similar. A search on Espacenet for US patents that fell into this classfication has identified 26,270 such patents in total, so there might be a lot more patents affected by this ruling.

Many other patent owners in other business related areas besides security trading might also be at risk from this judgement, athough this will depend on how later courts choose to interpret the Alice ruling. This will no doubt play out over time, but it is safe to say that many of the patent owners that could be at risk are those with similar patents to the Alice patent.


Other uses for ‘Similar Patent Finder’ automated patent searches

Besides identifying companies that also might be affected by adverse judgements on patentability, these searches can be used for:

  • To understand the general area around a patent of interest. This patent of interest could be

    • a patent similar to an invention you considering whether to patent, or how to patent
    • a patent belonging to your organisation or your client
    • a patent belonging to a competitor
  • To help invalidate a patent. You might have searched and found a priar art patent which is very relevant – but does not fully disclose the patent you are trying to invalidate. Nonetheless, some of the patents close to this may be the knockout patent you are looking
  • To strengthen your legal position around a patent of interest. This patent might be your patent, or a competitors patents. By identifying the most similar patents, you might be able to license or acquire these to strenghten your legal position. 

It should also be noted that AmberScope can also be effectively used for similar seaches. We do recognise though  that some users prefer the option of an automated patent search, and the Similar Patent Finder has been developed for this reason.


Other patents of interest to yourself or your clients?

Want to understand the most similar reports to a patent you are interested in? Our Similar Patent Finder searches are available from just US$300 – further details are found here.

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Finding licensing candidates for lowly cited patents – a ‘cheesy’ case study

How do you find licensees for lowly cited patents?  

In an ideal world, all of the patents you own or manage would have a wide range of forward citations, allow you to peruse this list to find the most likely licensees. However not all patents have a good number of forward citations, but sometimes you still need to find commercial opportunities for them, even if prior to the potential culling of these patents. We know this because Ambercite has already undertaken a number of searches for commercial opportunities for lowly cited patents.

Back in September 2013 we showed how the tools available in AmberScope can assist with this type of search, with a case study based on a lowly cited patent owned by Cornell University for a “Flavourful Low Cheese‘, being US6808735. 



Since then we have developed our Automated Reports, which include a licensee search report targeted at finding later patents that are similar to a patent of interest – but where existing citation links may not be published.

With the release of these reports, it is now time to return to the above case study. By returning to the same patents, we can directly compare the Automated Search Reports to what is possible in AmberScope.


Further details of the Automated Search Report service are found here. Of the available reports, we have chosen the “Licensee Finder” report, which is available for just $300 and a one to two day turnaround. The resulting report can be downloaded here, or by selecting the image below.


So what can we learn from this report?


1) There are just three forward citation patents – and two of them are filed by Cornell University

These apatents are, ranked in order of predicted similarity to US6808735:

  • Cornell University US20080233236, Simple mozzarella cheese-making methods, and US20080226767, Uniformly moist cheese
  • Schreiber Foods

So a more traditional patent citation analysis might presume that there is one interested party, namely Schrieber Foods. 


2) But there are a good number of later patents covering similar areas – even if these do not directly cited the Cornell cheese patent

The Licensee Finder report has identified these as being owned by:

  • Leprino Foods (13 patents)
  • Kraft Foods (3 patents)
  • New Zealand Dairy Board/[closely related] Fonterra  (2 patents)
  • Merchant Schmidt Incorporated
  • Spezialitäten-Käserei De Lucia 
  • Frito Lay
  • Tetra Lavel
  • Allied Blending and Ingredient
  • Spezialitäten-Käserei De Lucia 
  • Merchant Schmidt Incorporated
  • Arla Foods
  • Bel Fromageries 
  • Morinaga Milk Industry Co Ltd

This increases the number of potential licensing candidates up from 1 using conventional citation analysis up to 14 when using our Automated Reports.



Comparison to finding licensing candidates on Amberscope

The earlier blog, which applied a variety of search techniques within Amberscope,  had identified the following additional licensing candidates (when compared to conventional citation searching):

  • Leprino Foods
  • Land O’Lakes Inc, but this finding was based on an earlier filed patent – and so this information may be out of date.
  • Kraft Foods
  • Foremost Farms
  • Nestle
  • Cumberland Packing Company.

So the Automated Search Reports produce a slightly different set of results to what we we found on Amberscope. But the difference with the Automated Report is that:

  • The process is completely automated, so taking away the reliance of the operator when using AmberScope
  • The algorithms in the Automated Reports are highly tuned to find the licensees filing the most similar patents to the patent of interest – not just patents in the area.


Do you have a lowly cited patent(s) you are looking to find commercial opportunities for? Or even highly cited patent?  (our algorithms can easily deal with both)

If so, please send us the details of this patent(s) and within just one or two days you will have a similar list of potential licensing candidates for you to consider.

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Carnegie Mellon wins $1.54 billion. What other patents do they have?


Ambercite has previously covered both a prior art and licensee search for the patents behind the 1 billion patent judgement against Marvell, recently raised by Judge Nora Fischer to $1.54 billion. No doubt patent owners all over the world have looked at their patent portfolio and asked ‘do I have anything similar?’

To answer these sorts of questions, Ambercite has recently developed a portfolio review service. Advanced citation analytics are used to predict the relative importance of all of the patents in a portfolio, allowing rapid screening of what can be thousands of patents. To demonstrate the value of this review, we might go back to the Carnegie Mellon portfolio and ask the following two questions:

  • Would these advanced analytics suggest that the two patents successfully asserted against Marvell be worth investigating?
  • What other patents do Carnegie Mellon have? 


A portfolio report for the Carnegie Mellon is found here (or click on the image below).



Note that the report has two tabs:

  • A tab listing all patents, sorted in order of Amberscore, our predictor of patent importance
  • A tab only listing patents filed after 1995, again sorted in order of importance.  In this second tab, the two asserted patents are colour coded in yellow.

You will note a number of fields. Some of these are self-explanatory, and some require some explanation. Some of these fields are listed below, along with the values of these for the two Carnegie Mellon patents.



Value for US6439180 (percentile ranking compared to other post 1995 patents)

Value for US6201839 (percentile ranking compared to other post 1995 patents)



Patents with higher Amberscore values are more likely to be important inventions

6.4 (95%)

3.1 (79%)

Two of the higher ranked patents

Local dominance

Relative impact of patents compared to directly connected patents – highly values suggest dominant patents

95% (97%)

89% (92%)

Both are important patents in their field

Total number of forward citation patents

Often used to suggest important patents

74 (95%)

40 (83%)

Higher ranked patents

Number of forward citations filed in last 5 years

Shows if the invention is still relevant for new technologies

10 (82%)

4 (54%)

Weak evidence of current activity

Most common owners of forward citation patents (# of patents)

Shows who may be most likely to require a license

Marvell (24) Qualcom (18)

Marvell (10), Agere Systems (4) Infineon Technology (4)

Marvell are common forward citation owners

Most similar backward citation patent

Can help clarify the strength of the patent

US6201839, owned by Carnegie Mellon

US5689532, filed by Quantum Corp, now owned by Seagate


Most similar forward citation patent

Suggests most likely to be similar patent

US7000177, filed by Marvell

US6439180, owned by Carnegie Mellon, and with an Amberscore value of 4.6



This table suggests that it is not just the number of citations that matters, but also whom the citations are to. This model in turn allows us to review the rest of the Carnegie Mellon patents in the same light, namely looking for patents with:

  • Higher than average Amberscore values
  • Dominant in their field, i.e high Local Dominance values
  • Filed after 1995, so that there is some remaining patent left
  • Interesting list of leading owners of forward citation patents, maybe with a good number of forward citation patents from leading owners
  • Maybe the closest forward citation patent be to an interesting patent, or a patent owned by an interesting owner
  • And making some obvious checks that there is remaining life left in the patent and that it has not been abandoned.

These patents might have a greater than average chance of being licensed.

Or in other words, you should judge a patent not only by its numbers, but by its ‘friends’ as well.

From the tab of post 1995 patents included with the Carnegie Mellon spreadsheet , we can pick some patents that meet these criteria:

Patent number

Patent title

AmberScore (Local dominance)

Forward citation count (in last 5 years)

Interesting and leading owners of forward citation patents

Most similar backward citation patent, owner (Amberscore)

Most similar forward citation patent, owner (Amberscore)

US7056455 (2002)

Process for the preparation of nanostructured materials

11.0 (96%)

120 (41)




US7795355,  CARNEGIE MELLON (4.5)

US6084979 (1966)

Method for creating virtual reality

10.9 (95%)

130 (21)


US5850352, UNIV CALIFORNIA (24.0)

US6720949 PRYOR TIMOTHY, (4.7)

US7058873 (2002)

Encoding method using a low density parity check code with a column weight of two

9.3 (95%)

117 (61)



US7801200, AGERE SYSTEMS (12.8)

US5855000 (1996)

Method and apparatus for correcting and repairing machine-transcribed input..

9.0 (93%)

122 (26)

MICROSOFT (22),  IBM (10) ENGATE (8)

US5502774, IBM (7.5)

US6438523,  OBERTEUFFER JOHN A (3.9)

US7269516 (2002)

Systems and methods for monitoring behavior informatics

8.8 (90%)

68 (17)

IBM (5), SAS (5)

US7209588, CLEVER SYS INC (3.2)

US7580798,  PSYCHOGENICS (2.9)

US7616412 (2006)

Perpendicular spin-torque-driven magnetic oscillator

7.2 (81%)

70 (51)


US7471491, TOSHIBA (6.5)

US8264799,  TOSHIBA (9.6)

US6633182 (2001)

Programmable gate array based on configurable metal interconnect…

7.2 (83%)

58 (25)


US4197555,  FUJITSU (21.2)

US7446352, TELA INNOVATIONS (24.2)

US7194114 (2002)

Object finder for two-dimensional images, and system for determining a set of sub-classifiers.

6.8 (89%)

83 (27)



HP (14.7)

US7403643,  FOTONATION VISION (11.9)

US6625135 (1996)

Method and apparatus for incorporating environmental information for mobile communications

6.7 (84%)

89 (8)


US6252544, STEVEN HOFFBERG(16.7)

US7457289,  CISCO (4.7)

US6514259 (2001)

Probe and associated system and method for facilitating planar osteotomy during arthroplasty

6.6 (89%)

80 (13)


US6002859,  CARNEGIE MELLON (12.7)



Of course, none of this should be taken as a suggestion that any of the companies in the above table infringes any of the patents listed. Instead this is simply a demonstration of a systematic process that can be used to help identify patents in a large portfolio that may be worth investigating further.

And this is a simple and cost effective process. Thanks to our large and existing database of citation connections, Ambercite can produce a similar table to the Carnegie Mellon results for prices starting from US$500 for 200 patents, and we aim to produce this in less than 24 hours. Larger portfolios or multiple reports can attract further discounts.

Like to know more? Please contact us you would like one of these reports for a portfolio you might be managing or are interested in.



On another note, frequent readers might note that the Ambercite website has just had a big makeover. We hope that the new website is more user-friendly, and would be interested to hear any feedback that you have.



19 June 2014 update – Portfolio review of ~300 Microsoft “Android” patents

In a more recent blog, we apply a similar portfolio analysis to almost 300 patents licensed out to Android phone and tablet devices by Microsoft  – with this portfolio thought to earn Microsoft around $2 billion per annum.


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