Hardware-in-the-loop simulation

Hardware-in-the-loop (HIL) simulation, or HWIL, is a technique that is used in the development and test of complex real-time embedded systems. HIL simulation provides an effective platform by adding the complexity of the plant under control to the test platform. The complexity of the plant under control is included in test and development by adding a mathematical representation of all related dynamic systems. These mathematical representations are referred to as the “plant simulation”. The embedded system to be tested interacts with this plant simulation.

A HIL simulation must include electrical emulation of sensors and actuators. These electrical emulations act as the interface between the plant simulation and the embedded system under test. The value of each electrically emulated sensor is controlled by the plant simulation and is read by the embedded system under test (feedback). Likewise, the embedded system under test implements its control algorithms by outputting actuator control signals. Changes in the control signals result in changes to variable values in the plant simulation.

For example, a HIL simulation platform for the development of automotive anti-lock braking systems may have mathematical representations for each of the following subsystems in the plant simulation:

In many cases, the most effective way to develop an embedded system is to connect the embedded system to the real plant. In other cases, HIL simulation is more efficient. The metric of development and test efficiency is typically a formula that includes the following factors: 1. Cost 2. Duration 3. Safety 4. Feasibility

The cost of the approach should be a measure of the cost of all tools and effort. The duration of development and testing affects the time-to-market for a planned product. Safety factor and development duration are typically equated to a cost measure. Specific conditions that warrant the use of HIL simulation include the following:

Usage of HiLs enhances the quality of the testing by increasing the scope of the testing. Ideally, an embedded system would be tested against the real plant, but most of the time the real plant itself imposes limitations in terms of the scope of the testing. For example, testing an engine control unit as a real plant can create the following dangerous conditions for the test engineer:

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