Verification methodology provides robust embedded automotive electronics design

Currently, manufacturers are utilizing simulation-based methodologies earlier in the design process to verify that embedded automotive control algorithms and coordination strategies meet system performance requirements. The conventional methodologies, however, do not provide adequate techniques for analyzing the effects of system variability. But a verification methodology that takes advantage of "conserved" modeling and simulation techniques enables robust design of embedded automotive electronics software.

Verification methodologies
As shown below, automotive manufacturers today employ a variety of tools and techniques to validate embedded software throughout the design process. During the early stages of control development, designers can use a Model-Based Verification environment to create a model that represents the dynamic behavior of the plant and simulate its response (in non-real-time) to an algorithmic representation of the embedded control strategy. Rapid Prototyping techniques allow designers to evaluate the real-time performance of control strategies when they are connected to the actual plant, but before anything is committed to code. As control algorithms are implemented in software, Hardware-in-the-Loop (HIL) testing is used to verify the execution performance of the software running as targeted code on a microcontroller, in conjunction with a model of the plant dynamics being simulated in real-time.

While each of these techniques has importance in the automotive embedded software development process, they do not allow the designer to determine how system variability affects the ability of embedded software to control the system. The conventional approach to Model-Based Verification utilizes signal-flow modeling techniques for describing plant dynamics. The abstraction to the signal-flow domain makes it difficult to describe complex system behaviors at the depth required for sources of measured variation to be considered. Both Rapid Prototyping and HIL testing depend on the availability of physical hardware (prototypes)—but it is simply not practical to produce and test the number of prototypes required for a statistically significant analysis.

Conserved modeling and simulation
Conserved modeling techniques and system simulators overcome the limitations of the conventional signal-flow techniques for describing parameter variation and tolerances as part of a statistical analysis of the system. As the name implies, conserved system simulators enforce the laws of conservation of energy for the modeled system. For a given step in the simulation, iterative numerical methods are used to solve conservation laws (i.e. Kirchoff’s Current and Voltage Laws) for each node in the system. Mixed-Signal Hardware Description Languages (MSHDLs) allow designers to describe the dynamic behavior of a system as nonlinear differential algebraic equations in terms of the familiar notions of “through” and “across” variables that are specific to a given physical domain, as shown below.

Conserved modeling and simulation offer several benefits in the context of a Model-Based Verification methodology. The table below describes some of the benefits of conserved modeling and simulation in comparison to a signal-flow approach.