Author: Eric Walz
Imagine if two buyers bought the exact same year and made a vehicle, but one of those cars was on the road for 100,000 miles, while the other driver hit 200,000 miles before mechanical issues and wear and tear. do not encourage them to buy a new vehicle.
The identical vehicles purchased by both drivers were in a sense, mechanically and electrically the same, but one lasted 100,000 miles while the other driver was able to double the life to 200,000 miles.
So what was wrong with the car alone? It is most likely a lack of maintenance and individual driving habits that caused premature wear rather than manufacturing defects that shortened the life of the vehicle. But a new concept from automaker Porsche could help solve these types of service and maintenance issues in the future, including for electric vehicles.
Porsche has shared what it calls a “digital chassis twin” that can be used for predictive driving functions and the condition of a vehicle’s components.
The concept involves sensors embedded deep within the vehicle, including the chassis, which can determine if the vehicle is operating normally, while also identifying mechanical or electrical issues that require special attention.
According to Porsche, creating a virtual copy of an existing object (in this case a vehicle) enables data-driven analysis, monitoring and diagnostics without the challenges and constraints of real-world testing.
A vehicle’s so-called ‘digital twin’ includes not only the operating data it collects, but also all associated data, such as information collected during planned maintenance work and unscheduled repairs. Porsche claims that some elements of this digital twin already exist in ECUs and in databases kept at Porsche service centers.
A centralized intelligence system for data
The main advantage of vehicle “digital twins†is that they can be networked and that vehicle data, combined with a centralized intelligence system powered by AI, can determine whether a vehicle on the network is operating at its maximum, both mechanically and electrically.
For example, an algorithm can compare big data from centralized systems to data from sensors in the powertrain and chassis of a specific vehicle to identify a customer’s driving style or diagnose potential problems.
The algorithm can then recommend not only the optimum time for maintenance work on the vehicle, but also the required extent of such work based on the data from the integrated sensors.
More importantly, this data makes it possible to tailor service intervals to individual driving styles or to service specific components depending on how the customer uses their Porsche vehicle.
Similar types of sensors are already present in vehicles today, although they are not currently networked at a central location. An engine knock sensor, for example, is a piezo-ceramic sensor that picks up engine vibration to determine that fuel is burning properly and that “engine knock” from too low an octane is not occurring. not produced, which may cause damage.
If the engine knocking noises are picked up by the knock sensor, it sends a signal to the vehicle’s ECU to make small ignition timing corrections to eliminate it. These same concepts can be applied to EVs and powertrains to make sure everything is working properly by collecting and analyzing data from sensors and comparing it to big data from a fleet of normally operating vehicles.
Another advantage of this approach is that component wear and even faults can be identified before they are noticed by the driver, which is a significant advantage from a safety standpoint, according to Porsche.
Porsche software engineers have been working on the concept of the ‘digital twin’ for the past three years, focusing primarily on the chassis, known as the ‘chassis twin’. The project is managed by CARIAD, the autonomous automotive software company within the Volkswagen group.
In addition to data from Porsche vehicles, the project now has access to data from all vehicles in the Volkswagen Group, which increases the data pool by 20, according to Porsche.
Porsche said it started the project with a focus on the chassis components, as they are subjected to the highest loads, especially when the vehicle is used on racing circuits.
In-vehicle sensor technology as well as intelligent neural algorithms used for analysis detect the load on the chassis in the vehicle and return it to the driver.
This clever use of this data ultimately makes the vehicle safer, as any specific fault is identified immediately, even before the driver has to go to a repair shop for a diagnosis. As with people who see a doctor, vehicle problems are usually not noticed until symptoms appear, such as unusual noises coming from the vehicle. At this point, the repair may be more extensive and in many cases lead to other problems.
The digital chassis is already in use in the Porsche Taycan electric sedan. It is used to monitor the components of the vehicle’s air suspension. For now, the project is mainly to collect data on the acceleration of the body, which is then evaluated and transferred via Porsche Connect to the central backend system for analysis.
Next year, Porsche plans to launch the first digital twin and only data from sensors of mechatronic components will be evaluated. Other features will be added in the future, such as functions that allow the calculation of the wear of specific components without the need to use physical gauges.
For example, if multiple vehicles require the same alignment adjustment of their wheels or have a problem with the suspension component, the sensors could detect misalignment. Data collected from multiple vehicles may indicate a model that needs to be corrected.
The system constantly compares the data of each vehicle with the data of the fleet. The algorithms calculate the thresholds based on these results and, if exceeded, the customer can be notified via the on-board Porsche Communication Management System (PCM) that their vehicle’s chassis may need to be inspected at a facility. Porsche service.
This approach ensures that wear does not exceed specified limits and early repairs also help prevent further damage.
Although electric automaker Tesla does not use a digital twin concept like Porsche, the automaker can diagnose and correct potential problems with its vehicle in the same way by collecting data from the entire Tesla fleet. This data includes information on battery status and battery life, which can be processed if necessary through OTA software updates distributed to the entire fleet.
An example of this ability came in May 2018, when Consumer Reports (CR) published a report on poor performance of Model 3 brakes taking too long to stop. CR said braking performance was a “big flaw” and would no longer recommend the vehicle.
However, Tesla was able to release a software update that improved the braking distance of all Model 3. Shortly after, CR verified that the software update fixed the issue and put the Model 3 back on. its list of recommended vehicles.
Porsche aims to take this ability a step further by fixing any potential issues before a driver even realizes.
Another advantage of the technology is that these “digital records†can be used to show the residual value of a used vehicle, making the process of buying and selling used vehicles more transparent.
Automakers might consider offering an extended warranty based on documentation of component condition updates that may indicate that a vehicle has no problems at the time of sale. Individual data can also be used by dealers to set fair market prices for used models.
For chassis data collection for the Taycan, customers are asked through the PCM to consent to the data collection anonymously. Porsche said about half of all Taycan customers have agreed to participate in the pilot project, which the automaker says is an “incredibly positive response” to the application of the digital chassis.
