Virtual vehicle capabilities towards verification, validation and calibration of vehicle motion control functions

Detta är en Master-uppsats från KTH/Fordonsdynamik

Sammanfattning: Passenger safety and comfort are important aspects in the process of vehicle development. The world is heading towards developing the safest possible vehicle on the road. Using vehicle motion control functions is one of the ways to enhance vehicle stability. These motion control functions need to be developed in an energy optimised way. By complementing some of the development process with virtual models, both the development time and cost could be minimised. Hence, a sustainable way of control function development could be achieved. In order to verify, validate and calibrate vehicle motion control functions, an accurate model of the virtual vehicle is required. Hence, a research question on how good the virtual model needs to be for the purpose has been addressed. This report suggests a framework in order to determine the capabilities of a virtual vehicle.In this report, a comparison study has been carried out by exciting the real car and virtual model of a Volvo XC90 with a focus of covering the six degrees of freedom (Yaw, pitch, roll, longitudinal, lateral and vertical). A semi automated framework that possesses the capability of automating the testing in a virtual platform has been established. From the test results, the virtual vehicle capabilities were determined. Further, in the second part of the report, an example use case has been considered by taking two calibration sets of Electronic stability control (ESC) system in order to verify the previously established framework.The analysis includes various levels of plant and controller complexity such as Model-in-loop, Software-in-loop and Hardware-in-loop and on two different road surfaces, low friction and high friction. From the observations, the virtual models considered correlates well for the purpose of verification and validation. However, for the purpose of calibration, the models need to be fine-tuned in the virtual platform. Furthermore, the correlation on low friction road surface could be improved by simulating the tests using an advanced tyre model. Overall, this study helps in choosing the correct complexity of various subsystems in a vehicle for the purpose of verification, validation and calibration of vehicle motion control functions.

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