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Embedded systems continue to become more complex. As a result, more companies are utilizing model-based design (MBD) development methods and tools. The use of MBD methods and tools is helpful in increasing time to market and having instant feedback on the system design. One area that continues to mature is the testing and verification of the MBD systems. This paper introduces a hybrid approach to functional tests. The test system is composed of simulation software and real-time hardware. It is not always necessary to test a system in a real-time environment, but it is recommended if the goal is to deploy the system to a situation that requires real-time response. Vehicle drive cycles and powertrain control are utilized in this research as the example test case for this paper. In order to test the algorithms on a real-time system, it is necessary to understand the target controller's computing limitations and adjust the algorithms to meet these limitations.

In this study, an adaptive, supervisory, and hybrid fuzzy controllers as well as a fuzzy estimator are developed based on experimental and simulation data and expert's knowledge of the normal working of diagnostic systems. The advantage of the developed control system is that it has fewer parameters to tune; it also makes the system adaptable for changing environments or malfunctions; and provides the supervision of the overall performance of the engine management system. For the fuzzy estimator part of the system we employ the least square and gradient methods for the premise and consequent of the rule. This study introduces a new design method for FDI module. It also provides an efficient and easy to implement control system that can be incorporated into existing module with minimum changes, adjustment, and cost.