References
Bole, B., Daigle, M., Gorospe, G.,. (2014). Online prediction of battery discharge and estimation of parasitic loads for an electric aircraft. European Conference of the Prognostics and Health Management Society.
Bole, B., Teubert, C., Quach, C., Hogge, E., Vazquez, S., Goebel, K., & Vachtsevanos, G. (2013). SIL/HIL replication of electric aircraft powertrain dynamics and inner-loop control for V&V of system health management routines. Annual Conference of the Prognostics and Health Management Society.
Ceraolo, M. (2000, November). New dynamical models of lead-acid batteries. IEEE Transactions of Power Systems, 15(4), 1184-1190.
Chen, M., & Rincon-Mora, G.A. (2006, June). Accurate electrical battery model capable of predicting runtime and I-V performance. IEEE Transactions on Energy Conversion. 21(2), 504-511.
Daigle, M., Saxena A. & Goebel, K. (2012). An efficient deterministic approach to model-based prediction uncertainty estimation. Annual Conference of the Prognostics and Health Management Society, 2012.
Ely, J., Koppen, S., Nguyen, T., Dudley, K., Szatkowski, G., Quach, C., Vazquez, S., Mielnik, J., Hogge, E., Hill, B. & Strom, T. (2011). “Radiated Emissions From a Remote-Controlled Airplane - Measured in a Reverberation Chamber “. NASA/TM-2011-217146.
Hogge, E., Bole, B., Vazquez, S., Celaya, J., Strom, T., Hill, B., Smalling, K. & Quach, C. (2015). Verification of a remaining flying time prediction system for small electric aircraft. Annual Conference of the Prognostics and Health Management Society 2015.
Hogge, E., Bole, B., Vazquez, S., Kulkarni, C., Strom, T., Hill, B., Smalling, K., & Quach, C. (2017). Verification of prognostic algorithms to predict remaining flying time for electric unmanned vehicles. to appear in International Journal of Prognostics and Health Management, Vol. 8 doi: 2017
Hogge, E., Quach, C., Vazquez, S. & Hill, B. (2011). "A Data System for a Rapid Evaluation Class of Subscale Aerial Vehicle”. NASA/TM-2011-217145.
Julier, S. & Uhlmann, J. K. (1997). A new extension of the Kalman filter to nonlinear systems. In Proceedings of the 11th international symposium on aerospace/defense sensing, simulation, and controls (pp. 182-193)
Julier, S. & Uhlmann, J. (2004, March). Unscented filtering and nonlinear estimation. Proceedings of the IEEE, 92(3), 401-422.
Nelder, J. & Mead, R. (1965). A simplex method for function minimization. Computer Journal 1965; 7 (4), 308-313.
Quach, C., Bole, B., Hogge, E., Vazquez, S., Daigle, M., Celaya, J., Weber, A. & Goebel, K. (2013). Battery charge depletion prediction on an electric aircraft. Annual Conference of the Prognostics and Health Management Society 2013.
Saha, B., Koshimoto, E., Quach, C., Hogge, E., Strom, T., Hill, B., Vasquez, S. & Goebel, K. (2011). Battery health management system for electric UAV’s. IEEE Aerospace Conference. Big Sky, MT.
Saha, B., Quach, C. & Goebel, K. (2012). Optimizing battery life for electric UAVs using a Bayesian framework. 2012 IEEE Aerospace Conference.
Saxena, A., Celaya, J., Saha, B., Saha, S. & Goebel, K. (2010). Metrics for offline evaluation of prognostic performance. International Journal of Prognostics and Health Management, Vol. 1(1) 001, pp 13-15, doi: 2010
Saxena, A., Roychoudhury, I., Celaya, J., Saha, B., Saha, S. & Goebel, K. (2012). Requirements flowdown for prognostics and health management. Infotech@Aerospace Conference (pp. 8-9). Garden Grove, CA: AIAA, Reston, VA.
Saxena, A., Roychoudhury, I., Lin, W. & Goebel, K. (2013). Towards requirements in systems engineering for aerospace IVHM design. AIAA Conference, 2013. AIAA, Reston, VA.
Spiegel, M. R. & Stephens, L. J., (1998). Schaum’s outline of theory and problems of statistics. New York, NY: McGraw-Hill.
Zang, H., & Chow, M.-Y., (2010). Comprehensive dynamic battery modeling for PHEV applications. In IEEE power and energy society general meeting.