SIL Control Unit Simulation With Parallel Task Distribution
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Solution Overview
Problem
Existing software-in-the-loop (SIL) simulations for control units are inefficient due to suboptimal hardware utilization and lack of effective methods to minimize computing time.
Innovation Solution
A method is provided for configuring SIL simulations by ascertaining sporadic and periodic model components, creating parallelizable tasks, determining clock time points, and distributing tasks to virtual machines and processor cores to minimize computing time, including reconfiguration options such as changing periods, dividing tasks, and using faster processor cores.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If tasks are distributed to multiple virtual machines and processor cores, then computing time is reduced, but system complexity increases
Solution Approach 1:
The patent segments tasks into sporadic and periodic components, and further divides periodic tasks into parallelizable units that can be distributed across multiple virtual machines and processor cores. This segmentation enables efficient parallel processing while maintaining manageable system complexity through structured organization.
Solution Approach 2:
The patent introduces a multi-dimensional distribution architecture by mapping tasks across two dimensions: virtual machines (software layer) and processor cores (hardware layer). This dimensional approach enables comprehensive parallelization and optimizes computing time utilization without proportionally increasing perceived system complexity.
2Productivity
If the simulation runs in parallel on multiple processor cores, then productivity increases, but hardware requirements and complexity increase
Solution Approach 1:
The patent creates a universal task distribution framework that can operate effectively regardless of the specific number of processor cores or virtual machine configurations. The system adapts to different hardware setups by dynamically determining optimal task assignments, making the parallel processing capability universally applicable without requiring specialized hardware configurations.
Solution Approach 2:
The patent determines the smallest common multiple of all periods between clock time points of parallelizable tasks as a key parameter. This parameter optimization enables efficient parallel execution by synchronizing task schedules across multiple processor cores, maximizing productivity while minimizing the complexity of hardware coordination.
3Productivity
If task distribution is optimized to minimize computing time, then simulation efficiency improves, but configuration complexity increases
Solution Approach 1:
The patent performs preliminary analysis to ascertain sporadic and periodic model components before task distribution. By identifying and categorizing task characteristics in advance, the system can pre-determine optimal distribution strategies, reducing computing time while avoiding the need for complex real-time configuration adjustments.
Solution Approach 2:
The patent incorporates an optimization loop that evaluates task distribution effectiveness and adjusts assignments to minimize computing time. This feedback mechanism automatically optimizes the configuration based on actual performance data, improving simulation efficiency while keeping configuration complexity manageable through automated adjustment.
Data Source
AI summary
A method is provided for configuring an SIL simulation of a control unit running on a computer, software modules for the control unit, which have a plurality of tasks, being installed on the computer for the SIL simulation of the control unit, the tasks being processed in a predetermined clock cycle having a periodic period between the individual clock time points, and the computer including a plurality of processor cores, on which a plurality of virtual machines run, which each process predetermined tasks. A possibility is thus provided for minimizing the computing time of an SIL test.