AI-based virtual sensors are the main feature of our product. They are purely software-based and use standardly available signals of standard vehicles.
We use them to measure loads, like forces, torques, stresses, temperatures or electric currents. These loads wear and damage components like powertrain parts, chassis parts, brake systems, tires, the steering assembly or the batteries of electric vehicles.
Based on the loads measured by our virtual sensors we calculate precise usage profiles for the main components of each individual vehicle of a fleet. Comparisons show that the
signals of our virtual sensors match with high-quality and fidelity those of the physical sensors. This means that no additional sensor or hardware is necessary to monitor vehicle systems. Moreover, our virtual sensor technology can even replace existing hardware sensors.
Read more about our Virtual Sensors on
On our computation server – the AI Core – the data generated by the virtual sensors is enriched with meta-data like material characteristics, test rig results from development manufacturing information, weather conditions, etc. Finally, machine learning pipelines are applied, which learn from all these features and can thus exactly predict why, how and when a component will fail. On top, we also identify potential for design optimization and calculate residual value of vehicles based on their usage.
As shown below, all analyzed data can be managed and visualized through a web-based interface. The remaining lifetime predictions for the most important components of each individual vehicle are graphically depicted and the vehicle data is used to calculate possible material, CO2 and cost savings.
Through predictive analytics, COMPREDICT Virtual Sensors & Analytics helps you to avoid the failure of your vehicles due to unexpected damage and to optimize the design and construction of your own components.
Based on the information from the virtual sensors, we calculate usage profiles for all main components of each monitored vehicle.
Through our AI-based failure prediction and forecasting algorithm we are able to predict potential component failures and to apply predictive maintenance measures before the failure occurs. We have a focus on model interpretability to make causalities and correlations between the data visible.
Lighter & safer
By calculating exact usage and load profiles, overdesign and underdesign can be detected and eliminated. Our solution can save up to 15% of component weight and 5% of component costs.
At the same time, since all important components are monitored, it can be assured, that even for the most demanding driver no component fails prematurely or unexpectedly.
processes and testing
Our software helps to optimize the whole development process. All important data from development vehicles and series production vehicles is enriched by additional signals from our virtual sensors.
Based on this meaningful data real insights can be generated, which help to identify lightweight potentials and to design effective testing routines for the next generation of vehicles.
Precise value rating
for used cars
Based on the precise usage profiles generated by our virtual sensors, we use additional AI-based algorithms to precisely calculate the remaining value of a vehicle.
This enables us to provide a better estimation than the usual mileage-based way.
Would you like to learn even more about our product?
Visit us at Medium.com for detailed publications.
COMPREDICT was founded by Dr.-Ing. Rafael Fietzek and Dr.-Ing. Stéphane Foulard in 2016 in Darmstadt and has currently a team of 20 people from 8 different countries. Our focus lies on software-based load monitoring, failure probability calculation and life time prediction using AI and machine learning for mechanical, mechatronic, electric and electronic components . In the field of R&D, we supervise bachelor and master theses and offer internships.
COMPREDICT works worldwide with international automotive manufacturers and suppliers. We participated in the most renowned accelerator programs like Startup Autobahn in Germany in 2017, German Accelerator Tech in Silicon Valley in 2018 and PlugAndPlay Tech in Sunnyvale in 2019. We also won several prizes including the Johann Puch Open Innovation Award from MAGNA in 2016, the main and the special prize for Big Data at the “Gründerwettbewerb – Digitale Innovationen” from BMWi in 2017, and the second prize at the “Digitales Startup des Jahres” from BMWi in 2018. We have also been ranked in the top 50 Startups of 2018. In
march 2020 we successfully closed our second fundraising round to support our growth strategy.
You can get in touch with us using the contact form below or sign up for a free trial!
+49 (0)6151 3844614
64283 Darmstadt, Germany