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This paper addresses Hardware-In-the-Loop modeling and simulation for Diesel aftertreatment controls system development. Lean NOx Trap (LNT) based aftertreatment system is an efficient way to reduce NOx emission from diesel engines. From control system perspective, the main challenge in aftertreatment system is to predict temperature at various locations and estimate the stored NOx in LNT. Accurate estimation of temperatures and NOx stored in the LNT will result in an efficient system control with less fuel penalty while still maintaining the emission requirements. The optimization of the controls will prolong the lifespan of the system by avoiding overheating the catalysts, and slow the progressive process of component aging. Under real world conditions, it is quite difficult and costly to test the performance of a such complex controller by using only vehicle tests and engine cells.

Conventional hydraulic steering systems keep improving performance and driving comfort by introducing advanced features via mechanical design. The ever increasing mechanical complexity requires the advanced modeling and simulation technology to mitigate the risks in the early stage of the development process. In this paper, we focus on advanced modeling tools environment with an example of a load sensing hydraulic steering system. The complete system architecture is presented. Analytical equations are developed for a priority valve and a steering control unit as the foundation of modeling. The full version of hydraulic steering system model is developed in Dymola platform. In order to capture interaction between steering and vehicle, the co-simulation platform between the hydraulic steering system and vehicle dynamics is established by integrating Dymola, Carsim and Simulink.

This paper focuses on modeling of torque-biasing devices of a four-wheel-drive system used for improving vehicle stability and handling performance. The proposed driveline system is based on nominal front-wheel-drive operation with on-demand transfer of torque to the rear. The torque biasing components of the system are an electronically controlled center coupler and a rear electronically controlled limited slip differential. Kinematic modeling of the torque biasing devices is introduced including stage transitions during the locking stage and the unlocking/slipping stage. Analytical proofs of how torque biasing could be used to influence vehicle yaw dynamics are also included in the paper. A yaw control methodology utilizing the biasing devices is proposed. Finally, co-simulation results with Matlab®/Simulink® and CarSim® show the effectiveness of the torque biasing system in achieving yaw stability control.