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Faster race-car development with test data management in Motorsports

Motorsports is one of the most advanced industry and utilizes the latest technologies to become more competitive day by day. In fact, it’s an industry which is evolving at a very fast rate and makes use of test data at its best. This blog explains how motorsport teams can take maximum leverage out of the test data and its proper management to reduce the race car development time.

Why Test Data is important?

As the saying goes: You can’t improve it if you don’t measure it. In motorsports, Continuous improvement requires continuous measurement of all the possible parameters, and this is where the motorsport teams are moving to. Formula 1, the pinnacle of motorsports utilizes test data for continuously analysing and improving the car. The spontaneous decision making in Formula 1 races are fully driven by test data. Test data helps teams to predict the behaviour of race car in various scenarios and understand which parameters affect which other parameters and what must be done to improve the performance of the race car based on the past data. Race strategists use this to frame strategies for the race. Following image shows a few race car vehicle dynamics parameters mapped together.

Teams with facilities for instant availability, mapping and comparison of various parameters clubbed with experienced engineers can do wonders in motorsports. One great example for this is the Mercedes Formula 1 team. Data is one of the things that makes them the unbeatable in the mighty Formula 1. This is the reason why the motorsport teams are investing more in test data and test data management.

Test Data Management problems faced by Motorsport Teams?

Test Data management has become one of the key areas where motorsport teams are focussing on to advance themselves to reduce the race car development time and become more competitive. Teams face many problems with Test Data Management. The no: of parameters measured in the race cars are very large and it is measured for a long time continuously. This results in data coming in very large sizes and this size increases as teams participate in more races or when they do more testing. As the test data size keeps on increasing, management also becomes difficult. Following are few of the problems faced by the motorsport teams in Test Data Management

1. Absence of Traceability

A motorsport team will have lot of members and the test data will be scattered between the members. This means that data has been duplicated multiple times and different people do changes in different copies of data. It ends up in a situation where no team member knows when, which copy of the data was edited / manipulated and where is that copy of data. This results in the team members wasting a lot of time in finding where the required copy of test data is.

2. Loss of data

A major problem faced by motorsport teams is frequent resignation and addition of people. As the data is not stored in an organized manner and it is scattered in multiple systems, members frequently leaving the team will create problems in finding where the data is. There will be situations where data even gets lost and the team will be losing one of its valuable assets.

3. Shifting Locations

Teams must travel to different locations for testing and for races which means they must carry all the past data and the IT infrastructure to these places. Past data is very important as it is used to compare and analyse various scenarios and test cases. This leads to the team spending lots of resources for travelling and shifting.

4. Difficulties in Machine Learning & Predictive Analysis

Motorsport teams perform predictive analysis with machine learning using the past data. The size of this past data being big, it is always difficult and time consuming to find the required data from the huge chunk. This delays the whole predictive analysis processes which will eventually increase the race car development time.

5. Analysing Test Data

Test data analysis is a key part in race car testing. Usually, analysis is done manually by the team members. The team is losing its valuable time in doing these repetitive non-productive activities rather than using it for more important development activities.

All these problems are impacting badly on the efficiency of the team as a lot of time, effort and resources are wasted for managing the test data which if improved can reduce the overall time taken for the race car development.

How to solve these Test Data Management problems?

Motorsports teams and companies are now trying to automate the testing activities using technologies like telemetry, smart testing, etc. Many of them have started implementing the concept of smart testing in their organizations with software like ASI Datalab. Smart testing concept solves all the above-mentioned problems faced by teams in test data management. Smart Testing begins from the moment data is captured from the race car either from the racetrack during testing / race or from the rigs while testing and this data is uploaded into the centralized cloud server through plugins or through IoT devices securely. The moment data is on the cloud, it can be accessed, visualized and analysed by anybody from anywhere, be it the people sitting in the development centre or in different race locations, team management or the sponsors. The below diagram explains the concept of smart testing in detail.

How smart testing is useful in Motorsports?

Motorsports is an industry which is the most benefiting from smart testing. The data is stored in an organized and structured manner in the centralized sever. This prevents the data from getting lost and multiple copies of data being created. An automatic detailed activity log helps in complete tracking of who did what change in which data and where that data is and solves the traceability absence issue. All the data stored in an organized and structured manner in the centralized server means accessibility and utilization of the data for Machine learning & Predictive Analysis is easy. Team members are there in both test / race location as well as in the home development centre. Data captured from testing, different comparison results, ideas, etc. in tracks can be instantly shared with the members in the development centre. This provides the team a faster and quantified decision-making approach based on the data and opinions / suggestions from different experienced team members. Below image provides a pictorial representation of the use of smart testing in Motorsports.

Test Data Analysis is another area where motorsport teams are looking forward to saving time for faster race car development. The analysis of test data can be automated by creating the analysis process sheets once and using the same sheets later when new test data is captured. The team members need to focus only on the problematic areas where more attention must be given. This helps the team in saving time which they can invest in more testing or other development activities. Below image illustrates the process the automated test data analysis.

Apart from all these, smart testing concept involves all file formats to be supported in a same system without separate installations for different data formats. Smart Testing Software like ASI Datalab which works on the normal browser and being a cloud server-based platform, the problem of installations on multiple systems is eliminated. Most of the teams use the server provided by the software service provider itself. For Eg: ASI Datalab SaaS version provides both the software as well as the cloud server for the teams for monthly subscription packages. This helps the team in having a centralized platform for the whole testing activities and reduce the overall race car development time.

Formula Student is one motorsport which lacks behind in technological advancement compared to the other formula motorsports. Few teams have already started implementing smart testing concept in their teams which makes them more capable than the other teams. At the end of the day, what matters in motorsports is time, be it race car development time or the lap time.

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