The automotive industry is undergoing a transformative shift from hardware-driven vehicle development to software-centric, model-based validation practices. At the heart of this evolution is the demand for smarter, more adaptive cabin climate management systems. The Climate Control Module (CCM) a critical embedded ECU—regulates the vehicle’s Heating, Ventilation, and Air Conditioning (HVAC) functionality based on a fusion of passenger inputs and environmental sensor data. Traditionally, validation of such systems relied heavily on manual testing within climatic chambers or through in-vehicle trials using physical interfaces like the Climate Control Head (CCH) and the Infotainment Head Unit (HU). These legacy methods are increasingly inadequate in addressing rapid development cycles, high functional complexity, and stringent safety and quality standards.
This paper introduces a Digital Twin-enabled Hardware-in-the-Loop (HiL) testing methodology using advanced real-time controllers to simulate and validate the functionality of the CCM without the need for physical components. In this architecture, the real-time controller replicates the behavior of both the CCH (via LIN communication) and the HU (via CAN communication), effectively eliminating hardware dependency. Instead of using actual ECUs, the communication behavior of these interfaces is emulated using standardized LIN Description Files (LDF) and CAN Database Files (DBC), allowing precise simulation of user actions, message timing, and protocol-level error injection.
A significant innovation in this setup is the integration of a MATLAB/Simulink-based virtual HVAC plant model, forming a digital twin that accurately emulates cabin thermal dynamics, blower behaviour, air mixing mechanisms, actuator responses, and environmental sensor outputs. These simulations include:
• Solar Load Simulation: Adjusts cooling intensity based on virtual sun sensor input.
• Evaporator Sensor Behaviour: Ensures realistic control of refrigerant cycles and prevents freeze-over.
• Ambient and In-Cabin Temperature Sensors: Feed dynamic data for closed-loop HVAC control logic.
The real-time controller orchestrates closed-loop execution of the digital twin, interfacing with the CCM via CAN and managing real-world signal output to test actuators or feedback channels using hardwired and LIN-controlled signals. The controller’s deterministic execution ensures sub-millisecond synchronization of signal events, allowing robust testing of edge cases, transient failures, and precise time-sensitive operations such as PWM motor feedback or LIN/CAN communication faults.
To enhance testing efficiency, the framework supports full automation of validation cycles through real-time scripting interfaces and external test automation environments (e.g., Python-MATLAB APIs, custom GUIs). It covers a comprehensive range of use cases:
• Functional and performance testing across multiple temperature and load conditions.
• Robustness and fault injection testing, simulating conditions such as short-to-ground, signal interruptions, checksum failures, and sensor anomalies.
• Regression testing during iterative software development.
• Diagnostic validation under UDS (Unified Diagnostic Services) protocols.
Beyond meeting compliance and coverage goals, it enables faster detection of firmware defects such as missing state transitions, unresponsive actuators, synchronization mismatches, and sensor control logic failures long before integration into physical vehicle systems.
The proposed framework also serves as a foundation for future expansion, including:
• Integration of AI/ML-based climate prediction algorithms, leveraging occupant data, historical usage patterns, and external weather feeds.
• High-fidelity environmental modeling, simulating airflow, humidity, and passenger thermal sensation for enhanced comfort algorithms.
• Cloud-based test execution, allowing geographically distributed teams to collaborate and conduct HiL campaigns remotely.
• End-to-end system integration, enabling comprehensive vehicle-wide interaction by coupling the CCM HiL with other systems such as Body Control Modules, Battery Thermal Management Systems, and Autonomous Drive ECUs.
In conclusion, this Digital Twin-driven HiL architecture powered by real-time controllers transforms CCM testing from a static, hardware-reliant procedure into a scalable, intelligent, and agile validation platform. It supports faster development cycles, greater coverage of real-world and edge-case scenarios, and higher product maturity all crucial in delivering the next generation of thermally intelligent and user-adaptive climate control systems.