Communication framework for electrified off-road vehicles: a case study on the HHEA Compact Track Loader

Abstract

This thesis presents the development of a generalized, open-source software frameworkdesigned to support Controller Area Network (CAN) communication and visualization in electrified off-road vehicles. With the rising momentum toward electrification in heavy-duty and off-highway equipment, off-road platforms face unique challenges—including rugged operating conditions, high power demands, distributed control systems, and the integration of multiple electric actuators. These vehicles typically demand precise coordination and robust communication between subsystems such as traction, hydraulics, and auxiliary functions. To address these challenges, this work proposes a modular and extensible framework that is protocol-agnostic and configuration-driven. It supports decoding and encoding CAN messages via DBC files, enabling seamless integration across varied architectures. t its core, the framework incorporates a JSON-defined, condition-based finite state machine (FSM) responsible for managing vehicle states, enabling event- and threshold-based transitions, and handling fault detection in a thread-safe manner. Its lightweight and reusable design make it ideal for embedded software on vehicle control units (VCUs). The framework is validated through a case study on an electrified Compact Track Loader utilizing a Hybrid Hydraulic-Electric Architecture (HHEA), a research vehicle featuring five independently controlled electric motors in concert with a hydraulic common pressure rail system. Here, the hydraulic common pressure rails provide the majority of the power whereas the four of the electric motors modulate that power. The electric motors consist of two small traction motors, mounted in tandem with the left and right hydraulic propel motors, that deliver the modulating torques; two additional motors connected to two hydraulic pump/motors, which regulate pressure—and thereby force—for the lift and tilt hydraulic functions; and a primary electric motor that drives the Digital Displacement Pump (DDP), responsible for supplying flow to the common pressure rail. All hydraulic actuators operate in coordination with this common pressure rail system, which is dynamically supplied by the DDP based on real-time system demand. Coordinating these high-voltage subsystems requires a real-time, fault-resilient control strategy with reliable communication across a J1939-based CAN network. The vehicle’s architecture also includes a power distribution unit (PDU), battery management system (BMS), and several supporting ECUs, all integrated via the proposed framework. To aid in development and testing, a Qt-based dashboard is developed as part of the framework. This tool enables real-time monitoring and visualization of CAN signals, execution of control commands (such as vehicle start/stop and motor enable), and live diagnostic feedback during both bench and Hardware-in-the-Loop (HIL) testing. The dashboard supports additional features such as fault injection, data logging, and dynamic signal plotting, allowing developers to iterate quickly and verify functionality across diverse testing conditions. The framework’s open-source nature, combined with thorough documentation and modular software design, encourages adoption and customization across other electrified off-highway platforms. By abstracting protocol-specific logic and unifying control, diagnostics, and visualization under a single architecture, this work provides a scalable and reusable foundation for CAN-based communication in off-road electric vehicles. Through the successful implementation on the HHEA Compact Track Loader, this thesis demonstrates the feasibility and robustness of the proposed approach in managing multi-motor coordination, diagnostic visibility, and flexible software architecture in the context of next-generation electrified off-road systems.