Florian Rohde

Keynote Speaker |

  • Software Defined Vehicle
  • Electrification
  • OTA updates
  • Autonomous Driving
  • Silicon Valley
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Keynote Topics

Software Defined Vehicle (SDV)

Trends in the industry / Architecture / Technology / Solutions

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The term has been present in the industry for a while now, and it is a well used buzzword by start-ups to sell the idea of their importance in the future as well as by established OEMs and suppliers to signal that they are gearing up for the next big thing as well.
Now for about 10 or so years, there is a new generation of cars emerging and getting ready to take the relay from the EE era vehicles: The software defined vehicle. As the EE generation did not replace the established mechanical base of the vehicle but rather amended it, the SDV is also building on its predecessors. Given that fact, it is just fair to refer to evolution and not revolution.

So as I said, the SDV is still using a mechanical vehicle and a bunch of electronic control units. The difference now is that these control units act together rather than as individual controllers of components. Sure, there is still a physical distribution of controllers in many architectures, but this is changing. Generally, this 3rd vehicle generation can be seen as a complete system with subsystems and not as an orchestrated coexistence of many components. That being said, the architecture becomes centralized, there is shared calculation power, shared communication, and a design that allows the vehicle to act as one.
This centralized architecture gets accompanied by a new era of connectivity. These days cars can exchange data with the cloud at any time to achieve many new features, on one hand for the improvement of its own performance such as over-the-air software updates of predictive maintenance, and of course, to improve the user's wellbeing with information, infotainment, and communication.

A new approach in this generation of vehicles is the conditional existence of features. Customers get the option to book features temporarily, for example, assistant systems for the long road trip or pay-per-use fast charge support. And customers can add features after the initial vehicle purchase, maybe some budget freed up, or they learn about something later. Also interesting here is the used car market, where as a buyer, you can look for a car close to the configuration you like and then buy the missing features afterward. In many cases, this concept requires oversizing the hardware built into the cars, and many OEMs are working on a financially sane way to do so. On the other hand, it can also reduce the variety of hardware developed and saves costs that way.

Most important: the software defined vehicle is only successful when it is utilized properly, which means continuous improvements, over-the-air updates, and a growing pool of features, which also requires a change in mindset that the start of production means the end of development, can’t say that anymore.

Electrification

Gas vs hybrid vs battery vs hydrogen / Range anxiety / Charging networks

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Electrification is a very important topic in the automotive world today and it is the most pursued alternative propulsion method in the industry. There are two main options being worked on, battery energy storage or synthetic energy storage combined with a fuel cell electric generator. The electrification of a vehicle brings many new engineering challenges but also opportunities. Today's onboard electrical power sources are far superior to conventional 12V lead acid batteries alone. Modern power management is more involved than a simple float sensor in a gas tank and a dump battery.

The common discussion points about electric cars are usually the same: Range, range anxiety, charging stations and charging speed, and safety. With the addition of engineering background and experience reports, these discussions become especially intriguing. As a matter of fact, the vast majority of EV drivers have driven a car with a combustion engine before, so they have the experience to compare, while almost all of EV deniers have never driven an electric car.

Autonomous Driving

Challenges / Solutions / Validation / V2V and V2X / Technologies / State of the art

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Autonomous Driving is the hottest topic in both the industry and public domain. There are 6 levels of autonomy according to SAE, and while many cars today are supporting Level 2 already the industry rowed back from promising Level 4 or even Level 5 in the very near future. What are the reasons?

There are several challenges to overcome: Regulations, Technology, Validation and Public Acceptance, and all of them have to be solved before autonomous vehicles can be found around us in a significant number.

Regulations:

  • Where are autonomous vehicles allowed (Operational Design Domain -> ODD)?
  • Who is responsible in case of accidents?
  • How do cars talk to each other and to the infrastructure?

Technology:

  • How can weather conditions be handled?
  • How does the vehicle handle the enormous amount of data?
  • Train and run AI

Validation:

  • How much testing is sufficient?
  • Shared scenarios, labeling and taxonomy
  • Corner cases

Public Acceptance:

  • Is the public accepting autonomous vehicles when they are as good / 10 times better / 100 times better than human drivers?
  • Giving up owned mobility
  • Resistance against change

Over the Air Software Updates

Packaging / Connectivity / Data / Frequency / Acceptance / Risk

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Products that are improving over time are taking over the markets. Today a simple mobile phone device receives regular improvements and patches, and smart television sets download the newest firmware as soon as it is available. The automotive world right now is just getting started to explore the vast opportunities of updateable products. While there are small steps, mainly focused on infotainment systems for now, customers very soon will be able to choose between a car that is “final” when they buy it or a car that is offering new functionality over the time of ownership. Although there are a few that prefer the old school version the majority will turn towards the continuously improving products. Despite the clear advantage in initial customer acquisition there will be a completely new revenue stream of selling upgrades to existing owners, temporarily and permanently.

Another important driver for the need of OTA updates is the growing integration of transportation devices with each other and their environment, and the security risks coming with this. If there is a new vulnerability discovered in a product it has to be closed immediately in order to prevent risk to the users and the business.

So what is needed to get a system ready for OTA updates? There is an entire chain that has to be designed and maintained!

Continuous Integration & Validation

Fully integrated tool chains / End2End automation / Empowering CI in automotive

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End-to-end test automation on all integration levels is the key to reduce software delivery time from weeks to hours

Continuous integration has existed in the IT industry since the early 1990s. The basic approach behind the term is that new software is integrated, built and tested as often as possible rather than collecting all changes at the end of a development cycle. The advantages lie in the early detection of issues within the software code as well as in the integration. Problems can be pinpointed easier since the change content is kept small between testing cycles.

In order to achieve continuous integration a variety of tools and processes need to be in place. On the tool side it requires a common code repository with access to everyone involved in the development, integration of automated and self executing test suites on unit, component and system level as well as a feedback loop for results and issue reporting. There are also process steps necessary such as daily code commits, code verification in a cloned production environment before commit and a specific branching strategy.

The automotive industry has traditionally been working in silos with little to no interaction between the contributors until the very end. This concept requires very well specified requirements and extensive testing efforts but it does not prevent system integration issues early in the process. It is possible to achieve fully functional continuous integration and validation in the automotive world, as demonstrated during my tenure at Tesla where I designed a system that allows full vehicle software hotfix releases within hours instead of week.

Telematics

Data logging / Data selection / Data lake crawlers

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Telematics sounds like an old term, but is is more relevant than ever in the future of the automotive world. The word is mostly familiar from watching motor sports and hearing the pit crew receiving telematics from their race cars. And this is exactly what it is in the automotive world as well, just that the pit crew is the manufacturer or operator of the vehicles and the race cars are the entire fleet. Cars will be able to share information about their environment, weather and traffic situations and similar information with other cars. This are shared telematics, also known as V2V and V2X. Another kind of telematics is when the car reports its health and usage statistics.

Those can be utilized for tailoring a custom user experience and also to do preventive maintenance, for example suggesting a new part when the one in the car is showing a certain degradation. There are relatively simple telematics such as battery health statistics which are fairly easy to generate and to act on, and there is the large exabytes data stream generated by all computers in the vehicle. There are two ways of handling this amount of data: Evaluate the data at its source and decide what to send to the data lake (see AI in automotive on the edge) or send all data and run algorithms in the lake.

The question is what to do with these large amounts of data, what to get out of it. Today it is very common that these data lakes are only collecting data but there is no smart handling of that information. In order to get a value out of the massive data lake there must be an automated way of checking through the data with a high multiple of real time calculation.

Building and retaining teams

How to build / motivate / retain talent (I hired over 100 engineers during my career, and over 100 interns, flucutuation way below average)

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No matter if you are building a new team from scratch, growing an existing team or simply want to make your team happier, after you successfully found your top talent you want to apply a few principles to keep them happy, motivated, productive and on board for a long time.

You have to read your employees, some want to have more freedom, some want to hear very detailed instructions. This can be observed usually fairly easily, but you can also just ask them in a personal talk. Put those talks on the calendars on a regular schedule, take your time to hear from your reports whats going on in their world, what challenges are they dealing with, how can you help them. The best result is achieved when an employee is feeling empowered to act and responsible for their part of the product. Keep your team involved with the final product, let them see where they contribute, make them feel proud. Now you have a great employee that is motivated and powering through the challenges, how to keep that employee on board?

The answer is as simple as it is complicated: You have to fight for them! You are the firewall between your team and everything above and around, keep noise out, handle management turbulences, let your team do what they do best. You receive some ideas from them? Perfect, now do everything you can to help them implement them, sometimes a little thinking outside of the box might be required, and many ideas develop while figuring out the quirks, just don’t tell them “no” without coming up with an alternative.

And last but not least: Work is pretty serious stuff, so from time to time get your staff together and do something silly!

Silicon Valley Firechats

Challenges for German companies / Idiosyncrasies / Anecdotes / Future prospects

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Just some chatting, story telling, anecdotes, you name it.

Nothing suitable found?

Please contact me if you'd like to combine any of the above listed topics individually suited to your event.

Innovator.

More than 15 Years Industry expertise.
From start-ups to global players.

"Florian has been a terrific speaker at our events. He has engaged our audience with his passion, his unique industry expertise and his entertaining on-stage presence. – Eric Starkloff, President and CEO at National Instruments

Testimonials

Expertise / Insights / Passion

"We book Florian every time we bring a group of executives into Silicon Valley. His insights into the rise of Tesla and also all the other cutting edge companies are very valuable for our clients."

Thomas Armbruester – Prof. at Univ. of Marburg, and Owner, Prof. Armbrüster Leadership Services GmbH

"I worked with Florian at Tesla and NIO, in both companies he assembled the system validation team and architected and implemented automated system validation infrastructure from scratch to a ludicrous speed release machine"

Robert Herb – Director of Livewire Labs at Harley-Davidson

Experience

iProcess / 2019 – TODAY

System Integration and Validation Strategy Consultant

NIO / 2018 – 2019

Director System Integration and Validation

Tesla / 2012 – 2018

Sr. Manager Firmware System Validation

Continental / 2007 – 2012

Group Leader System Development and Validation

System Validation Manager and System Integration Engineer

SiemensVDO Automotive / 2005 – 2007

System Validation Engineer

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Consulting

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iProcess was founded 2014 with the goals to help bringing automotive products into this world, better and faster. We provide the best industry-driven consulting experience and offer easy, simple and scalable solutions based on our clients' needs.

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