This thesis presents a simulation model for a Control Area Network (CAN) software stack, the Dual FIFO CAN (DFC) stack, and a method for identifying and incorporating the details of the host environment (hardware setup, operating system, etc.) into the implementation of the simulation model in order to achieve a high level of fidelity. The method enable the simulation model to produce more realistic simulation results that are close to real-life experiments of the target system compared to existing commercial and academic simulation tools, which mostly ignore the system details
The simulation model is implemented based on the specification documents of the DFC stack as well as knowledge gained from real-life experiments about the DFC stack and its host environment, a dual-core Electric Control Unit (ECU) hardware test bench that runs a Real-Time Operating System (RTOS). Like the actual DFC stack, the simulation model offers features such as dual non-preemptive FIFO transmit queues and TX buffers, and reserved slots in the queues for higher-priority messages. By using the method introduced in this research, the simulation model also offers options, once enabled and configured with proper parameters, for simulating a host environment that has effects on the behaviors of the modeled CAN stack. And these features are not fully available in existing commercial and academic simulation tools.
The model provides internal calibration values of the DFC stack as configurable parameters to the user, making it easy to customize the simulation.
Configurable calibration values includes the total number of slots in the transmit FIFO queues, number of reserved slots in the queues, transmit-rate thresholds that decide to which transmit queue a message is routed and whether a message is eligible to enter the reserved slots of the queues, and together they determine the queuing behaviors of the DFC stack. The options for simulating a host environment (an ECU on a CAN network in a modern vehicle, for instance) is capable of recreating the timing effects (delays, jitters or other effects due to the processing load, physical limitation and internal implementation) of the target host environment on the simulation results. Both deterministic (constant values, etc.) and/or statistical (probability distributions, etc.) models can be used to configure each single timing effect from the simulated host environment.
The simulation model is also automated to transmit a set of customized transmit message (configurable message ID, DLC, period and internal transmission priority) and process simulation results according to the purpose of the simulation (statistical analysis, plots of data, etc). These features make it possible for the simulation model to be used not only to simulate various customized simulation scenarios, but also for different purposes in various stages of the development process, for instance, a pre-experiment simulation run before a test bench experiment to test the correctness of the calibrations and predict the possible outcomes of the experiment, or, simulations for confirmation purposes in order validate the test bench data after the test experiment. The model is compatible with typical modeling, simulation and development environments as it is implemented in MATLAB SimEvents environment, which works with third-party CAN development tools such as Vector CANoe. It is also designed to work with the high-fidelity model of the Vector CAN protocol stack from Whinton (2016). / Thesis / Master of Applied Science (MASc)
| Identifer | oai:union.ndltd.org:mcmaster.ca/oai:macsphere.mcmaster.ca:11375/22847 |
| Date | January 2018 |
| Creators | Qian, Zhizhao |
| Contributors | Lawford, Mark, Wassyng, Alan, Computing and Software |
| Source Sets | McMaster University |
| Language | English |
| Detected Language | English |
| Type | Thesis |
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