​Accelerating Vehicle Durability Testing with StellarAi

​Background:

StellarAi, our advanced software solution, was seamlessly integrated into Fleet Durability Testing operations with one of our esteemed OEM Customers. The test fleet, comprising 10 vehicles, diligently collected data over the CAN network during 8 to 10-hour runs each day.

​Before StellarAi:

Previously, the data acquisition process was labor-intensive. Retrieving data from CAN data loggers and manual processing consumed a significant amount of time, averaging 1 to 2 hours per vehicle per day. This manual effort was followed by manual data analysis, resulting in higher test to report times – often taking up to 1 week.

After StellarAi:          

With StellarAi in place, efficiency soared. The integration streamlined data management, allowing for the systematic tagging and processing of incoming data packets from DAQ devices installed in each vehicle. Preconfigured analysis requirements facilitated near real-time processing of data at both the Message and Signal levels, empowering the client's personnel.

Moreover, report generation underwent a remarkable transformation. Reports were now pre-defined and scheduled within StellarAi, automating the process. As a result, Test Engineers received auto-generated reports summarizing the previous day's durability test runs promptly at 9 AM each morning.

Conclusion: 
StellarAi implementation led to significant time savings, with over 65% reduction in data analysis and report generation efforts.

All test data was efficiently consolidated and managed in real-time within the OEM's secure Data Lake.

​Efficient Troubleshooting of Field Early Warranty Issues with StellarAi

​Background:

The DriveTech team was tasked with addressing a critical Field Early Warranty issue for one of our valued Customers. The focus was on an Electric Vehicle (EV) experiencing sporadic and abrupt shutdowns. The challenge lay in recording CAN data from the vehicle and swiftly identifying the root cause of the problem.

​Before StellarAi:

Initial attempts involved engineers replicating the failure event and meticulously recording CAN data. However, the sheer volume of data amassed from a single vehicle, totaling approximately ~100 GB across 500+ files, presented a daunting challenge. Each file demanded approximately 45 minutes for thorough analysis, translating to an arduous month-long endeavor to scrutinize all files.

After StellarAi: 

The introduction of StellarAi revolutionized the troubleshooting process. All test data was seamlessly transmitted to StellarAi from the Data Logger via wireless connectivity. Upon data availability, Test Engineers swiftly pinpointed the precise event using StellarAi's Advanced Search & CAN Message Data analysis capabilities.

Furthermore, StellarAi empowered Test Engineers to effortlessly merge and visualize multiple large files, a feat previously fraught with complexity. This accelerated the diagnosis process, significantly mitigating the impact on the Customer's reputation.

Conclusion: 

Thanks to StellarAi, the Customer achieved remarkable efficiency gains. What previously required over 30 days of data analysis was condensed into a single day. Rapid identification of the root cause of the issue not only expedited resolution but also bolstered the Customer's confidence in our capabilities.

​Efficient EV Range Testing with StellarAi

​Background:                    

DriveTech assisted one of its OEM Clients in conducting Electric Vehicle (EV) range calculations in accordance with the NEDC STP Drive Cycle. This involved driving the vehicle on a chassis Dyno, following the NEDC STP sequence, and recording data via the vehicle’s CAN Network.

​Before StellarAi:

The data logging process resulted in over 100 files, each exceeding 100 MB in size. Test Engineers faced a significant time commitment, requiring approximately 15 to 20 days to manually analyze each file and subsequently integrate the findings to determine the EV range accurately.

After StellarAi: 

DriveTech revolutionized the process by embedding the NEDC standard document directly into StellarAi as an 'Analytical Template'. This innovative approach streamlined the process significantly: Engineers simply executed the template on the test data files, and StellarAi swiftly computed the EV range and other vital statistics in less than 5 minutes.

Conclusion: 

The implementation of StellarAi empowered the Customer to expedite EV range calculations with unprecedented ease. What once demanded a labor-intensive manual analysis process was now accomplished within a couple of clicks. This not only saved valuable time but also enhanced overall efficiency, enabling Test Engineers to focus on more strategic initiatives.

​​Intelligent Analysis of J1939 Data

​Background:     

DriveTech team was tasked with addressing a critical Field Early Warranty issue for one of our valued Customers. The focus was on an Electric Vehicle (EV) experiencing sporadic and abrupt shutdowns. The challenge lay in recording CAN data from the vehicle and swiftly identifying the root cause of the problem.

​Before StellarAi:  

Initial attempts involved engineers replicating the failure event and meticulously recording CAN data. However, the sheer volume of data amassed from a single vehicle, totaling approximately ~100 GB across 500+ files, presented a daunting challenge. Each file demanded approximately 45 minutes for thorough analysis, translating to an arduous month-long endeavor to scrutinize all files.

After StellarAi: 

The introduction of StellarAi revolutionized the troubleshooting process. All test data was seamlessly transmitted to StellarAi from the Data Logger via wireless connectivity. Upon data availability, Test Engineers swiftly pinpointed the precise event using StellarAi's Advanced Search & CAN Message Data analysis capabilities.

Furthermore, StellarAi empowered Test Engineers to effortlessly merge and visualize multiple large files, a feat previously fraught with complexity. This accelerated the diagnosis process, significantly mitigating the impact on the Customer's reputation.

Conclusion: 

Thanks to StellarAi, the Customer achieved remarkable efficiency gains. What previously required over 30 days of data analysis was condensed into a single day. Rapid identification of the root cause of the issue not only expedited resolution but also bolstered the Customer's confidence in our capabilities.

* More use cases coming soon....