In this paper, we show how Model-Based Design can be applied in the development of a hybrid electric vehicle system. The paper explains how Model-Based Design begins with defining the design requirements that can be traced throughout the development process. This leads to the development of component models of the physical system, such as the power distribution system and mechanical driveline. We also show the development of an energy management strategy for several modes of operation including the full electric, hybrid, and combustion engine modes. Finally, we show how an integrated environment facilitates the combination of various subsystems and enables engineers to verify that overall performance meets the desired requirements.
This article presents a methodology to apply Model-Based Design to develop and automatically optimize vehicle stability control systems. Such systems are employed to improve the dynamic rollover stability of Sport Utility Vehicles (SUVs). A non-linear vehicle model, representative of a midsize SUV, was built in CarSim®. This vehicle model is used in Simulink® to design a control system that reduces the risk of rollover. Optimization methods are then used to automatically adjust controller parameters to meet the system specifications that ensure the stability of the vehicle. Cosimulation between the two software packages enables rapid design and verification of control algorithms in a virtual environment. The results of the simulation experiments can be visualized through a 3-D animation of vehicle motion. The control system is adapted for the specific vehicle model, enabling it to remain stable under standard test conditions. The National Highway Traffic Safety Administrations' (NHTSA) fishhook maneuver was used to estimate dynamic rollover stability of the vehicle and benchmark the performance of the SUV both with and without the optimized controller.
This paper uses commercial off-the-shelf (COTS) domain specific modeling software to create a high fidelity plant model of an aircraft's landing gear for inclusion into a full aircraft flight simulator. The use of domain specific modeling software enables detailed modeling of the physics and facilitates accurate computational simulation of the aerodynamic and mechanical loads that occur when the landing gear are deployed and retracted during landing and take-off operations. The parameter design space is easily searched by considering a number of different landing scenarios including touching down on one wheel first, to optimize the design.
In this paper we will demonstrate the multi-user collaborative enhancement of a Simulink model of the NASA HL-20 with the goal of designing a new multi-loop, multicomponent approach and landing control system. The model is maintained using a CVSbased configuration management system by multiple engineers. Using this model the approach and landing guidance control systems are designed with commercial off-the-shelf software. The control system is developed in a single design environment using a single model which gives insight into design trade-offs and loop interactions from a system-wide perspective. The workflow and tools that were used will be presented to coordinate with the modeling and control design work that was progressing simultaneously during the course of this project.
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