Abstract: Good estimates of vehicle mass and road grade are important in automation of heavy duty vehicle, vehicle following maneuvers or traditional powertrain control schemes. Recursive Least Square with multiple forgetting factors accounts for different rates of change for different parameters and thus, enables simultaneous estimation of the time-varying grade and the piece-wise constant mass. An ad-hoc modification of the update law for the gain in the RLS scheme is proposed and used in simulation and experiments. We demon-strate that the proposed scheme estimates mass within 5 % of its actual value and tracks grade with good accuracy provided that inputs are persistently exciting. The experimental setups, signals, their source and thei...
This work provides novel robust and regularized algorithms for parameter estimation with application...
A recursive least square (RLS) algorithm for estimation of vehicle sideslip angle and road friction ...
This study presents a vehicle mass estimation system based on adaptive extended Kalman filtering wit...
This Master’s thesis describes a method for real-time estimation of a vehicle’s mass for automobiles...
We introduce a recursive generalized total least-squares (RGTLS) algorithm with exponential forgetti...
An accurate estimate of the mass of a passenger vehicle is important for several safety systems and ...
This thesis describes development of a real-time-implementable algorithm for simultaneous estimation...
In this report a recursive least square scheme with multiple forgetting factors is proposed for on-l...
To solve the vehicle mass estimation problems, two vehicle mass estimation methods based on both com...
As active chassis controllers are becoming increasingly complex and sophisticated, the performance o...
The gross vehicle mass (GVM) and the road grade are two factors that both have a substantial influen...
We introduce an incremental total least-squares vehicle mass estimation algorithm, based on a vehicl...
This dissertation uses polynomial chaos theory to address recursive parameter estimation in state sp...
Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction...
In adaptive control and online parameter estimation, recursive identification algorithms, such as Re...
This work provides novel robust and regularized algorithms for parameter estimation with application...
A recursive least square (RLS) algorithm for estimation of vehicle sideslip angle and road friction ...
This study presents a vehicle mass estimation system based on adaptive extended Kalman filtering wit...
This Master’s thesis describes a method for real-time estimation of a vehicle’s mass for automobiles...
We introduce a recursive generalized total least-squares (RGTLS) algorithm with exponential forgetti...
An accurate estimate of the mass of a passenger vehicle is important for several safety systems and ...
This thesis describes development of a real-time-implementable algorithm for simultaneous estimation...
In this report a recursive least square scheme with multiple forgetting factors is proposed for on-l...
To solve the vehicle mass estimation problems, two vehicle mass estimation methods based on both com...
As active chassis controllers are becoming increasingly complex and sophisticated, the performance o...
The gross vehicle mass (GVM) and the road grade are two factors that both have a substantial influen...
We introduce an incremental total least-squares vehicle mass estimation algorithm, based on a vehicl...
This dissertation uses polynomial chaos theory to address recursive parameter estimation in state sp...
Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction...
In adaptive control and online parameter estimation, recursive identification algorithms, such as Re...
This work provides novel robust and regularized algorithms for parameter estimation with application...
A recursive least square (RLS) algorithm for estimation of vehicle sideslip angle and road friction ...
This study presents a vehicle mass estimation system based on adaptive extended Kalman filtering wit...