Implementing Remote CAN/LIN Diagnostics in Electric Bus Fleets: A Case Study on VDL Bus & Coach Using Wi-Fi Data Loggers

Abstract

Intermittent faults in modern electric and hybrid buses present a significant challenge for fleet diagnostics and maintenance. This paper examines the implementation of the CANedge2 Wi-Fi-enabled CAN/LIN data logger in the VDL Bus & Coach fleet. By enabling remote data access and over-the-air configuration, the system reduced technician workload, minimized vehicle downtime, and streamlined the diagnostic process. The case study highlights the advantages of cloud-integrated logging systems in public transportation fleets and proposes a scalable model for telematic diagnostics.

1. Introduction

The increasing electrification of public transport vehicles has introduced new challenges in fault detection and maintenance. Traditional diagnostics require on-site visits to manually connect and retrieve log data from CAN/LIN networks. This process is time-consuming and cost-intensive, particularly when dealing with faults that are intermittent or occur under specific conditions. VDL Bus & Coach Belgium, a manufacturer and operator of electric and hybrid buses, sought to improve this process by implementing a remote diagnostic system leveraging modern CAN data logging technologies.

2. Problem Statement

Intermittent fault events in VDL buses frequently necessitated up to three separate technician visits: initial deployment of a data logger, retrieval of the device following a fault, and post-analysis support. This approach incurred high labor costs and often delayed root cause identification. Additionally, collecting complete raw CAN logs generated excessive data volumes, complicating analysis and increasing wireless upload costs.

3. Methodology

To address these inefficiencies, VDL deployed the CANedge2 dual-channel CAN/LIN data logger across selected vehicles in their fleet. Key deployment parameters included:

Wi-Fi Upload via LTE Hotspot: Data log files were automatically uploaded to a secure AWS S3 bucket upon detection of a fault.

Remote Configuration via CANcloud: Technicians could update the logger’s configuration files over the air to change filters, logging intervals, or diagnostics triggers without accessing the vehicle.

Custom Filtering: Targeted message filtering reduced log size by up to 90%, optimizing wireless data transfer and log relevance.

Driver-Triggered Logging: Operators manually noted time of faults, allowing engineers to quickly extract precise log segments for offline analysis.

This approach was supplemented by the use of open-source data conversion tools and dashboards for efficient post-processing.

4. Results

Initial deployment demonstrated measurable operational benefits:

Reduced Technician Visits: Physical site visits were reduced from three per incident to one or two.

Faster Diagnosis: Remote access to timestamped logs enabled near real-time analysis of intermittent faults.

Optimized Data Management: Custom filtering minimized log sizes, reducing data upload costs and simplifying analytics.

Improved Fleet Uptime: Reduced diagnostic delay translated to less time off-road for affected vehicles.

5. Discussion

The results confirm the utility of CANedge2 as a scalable, low-overhead diagnostic solution for electric and hybrid bus fleets. Its ability to function as a standalone logger, combined with secure remote data upload and reconfiguration, distinguishes it from traditional data logging and OBD scan tools. The case highlights the importance of intelligent filtering and modular architecture in modern telematics, especially where network bandwidth and technician availability are limited.

Moreover, the approach aligns with industry trends toward predictive maintenance and condition-based monitoring, which are vital for electric fleets due to their complex electronics and software-dependent components.

6. Conclusion

This study demonstrates that remote CAN/LIN logging with the CANedge2 significantly improves diagnostic efficiency in electric public transport fleets. By reducing technician involvement, enabling real-time data access, and improving analytic precision, VDL Bus & Coach achieved operational cost savings and enhanced vehicle uptime. These findings suggest that similar fleets may benefit from adopting Wi-Fi-enabled data loggers as part of a broader fleet telematics and diagnostics strategy.

References

CSS Electronics. (2023). Electric Bus Telematics: Remote J1939 Diagnostics via CANedge2 – VDL Bus & Coach Case Study. Retrieved from https://www.csselectronics.com/pages/electric-bus-telematics-remote-j1939-vdltelematics-remote-j1939-vdl