A retrofittable intelligent vehicle performance and fuel economy maximization system would have widespread application to military tactical and non-tactical ground vehicles as well as commercial vehicles. Barron Associates, Inc. and Southwest Research Institute (SwRI) recently conducted a research effort in collaboration with the U.S. Army RDECOM to demonstrate the feasibility of a Fuel Usage Monitor and Economizer (FUME) – an open architecture vehicle monitoring and fuel efficiency optimization system. FUME features two primary components: (1) vehicle and engine health monitoring and (2) real-time operational guidance to maximize fuel efficiency and extend equipment life given the current operating conditions. Key underlying FUME technologies include mathematical modeling of dynamic systems, real-time adaptive parameter estimation, model-based diagnostics, and intelligent usage monitoring. The research included demonstration of the underlying FUME technologies applied to a vehicle simulation constructed using SwRI’s RAPTORTM software toolkit and to LMTV and MRAP vehicle data sets collected under the AMSAA Sample Data Collection (SDC) effort.
[1]
Bengt Schmidtbauer,et al.
Road Slope and Vehicle Mass Estimation Using Kalman Filtering
,
2002
.
[2]
C. Vogel.
Computational Methods for Inverse Problems
,
1987
.
[3]
Rick Chartrand,et al.
Numerical Differentiation of Noisy, Nonsmooth Data
,
2011
.
[4]
Hiroshi Ohnishi,et al.
A study on road slope estimation for automatic transmission control
,
2000
.
[5]
Karl Henrik Johansson,et al.
Improved road grade estimation using sensor fusion
,
2006
.
[6]
M. Barth,et al.
Heavy-Duty Diesel Vehicle Fuel Consumption Modeling Based on Road Load and Power Train Parameters
,
2005
.
[7]
M. Arndt,et al.
Identification of road gradient and vehicle pitch angle
,
2004,
Proceedings of the 2004 IEEE International Conference on Control Applications, 2004..