Nonlinear Observers based on the Functional Mockup Interface with Applications to Electric Vehicles
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[1] Lennart Ljung,et al. System Identification: Theory for the User , 1987 .
[2] D. Simon. Optimal State Estimation: Kalman, H Infinity, and Nonlinear Approaches , 2006 .
[3] Hilding Elmqvist,et al. Modelica — A unified object-oriented language for physical systems modeling , 1997 .
[4] Jonathan Brembeck,et al. A real time capable battery model for electric mobility applications using optimal estimation methods , 2011 .
[5] Andreas Junghanns,et al. The Functional Mockup Interface for Tool independent Exchange of Simulation Models , 2011 .
[6] L. Imsland,et al. Constrained state estimation using the Unscented Kalman Filter , 2008, 2008 16th Mediterranean Conference on Control and Automation.
[7] James Demmel,et al. LAPACK Users' Guide, Third Edition , 1999, Software, Environments and Tools.
[8] D. Simon. Kalman filtering with state constraints: a survey of linear and nonlinear algorithms , 2010 .
[9] Michel André,et al. The ARTEMIS European driving cycles for measuring car pollutant emissions. , 2004, The Science of the total environment.
[10] Niels Kjølstad Poulsen,et al. Incorporation of time delayed measurements in a discrete-time Kalman filter , 1998, Proceedings of the 37th IEEE Conference on Decision and Control (Cat. No.98CH36171).
[11] M. Otter,et al. Modelica - A Unified Object-Oriented Language for Physical Systems Modeling - Language Specification , 2000 .
[12] Rudolph van der Merwe,et al. The square-root unscented Kalman filter for state and parameter-estimation , 2001, 2001 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.01CH37221).
[13] Johann Bals,et al. ROMO - THE ROBOTIC ELECTRIC VEHICLE , 2011 .