Online identification of a two-mass system in frequency domain using a Kalman filter

Some of the most widely recognized online parameter estimation techniques used in different servomechanism are the extended Kalman filter (EKF) and recursive least squares (RLS) methods. Without loss of generality, these methods are based on a prior knowledge of the model structure of the system to be identified, and thus, they can be regarded as parametric identification methods. This paper proposes an on-line non-parametric frequency response identification routine that is based on a fixed-coefficient Kalman filter, which is configured to perform like a Fourier transform. The approach exploits the knowledge of the excitation signal by updating the Kalman filter gains with the known time-varying frequency of chirp signal. The experimental results demonstrate the effectiveness of the proposed online identification method to estimate a non-parametric model of the closed loop controlled servomechanism in a selected band of frequencies

Online Identification of a Mechanical System in the Frequency Domain with Short-Time DFT

A proper system identification method is of great importance in the process of acquiring an analytical model that adequately represents the characteristics of the monitored system. While the use of different time-domain online identification techniques has been widely recognized as a powerful approach for system diagnostics, the frequency domain identification techniques have primarily been considered for offline commissioning purposes. This paper addresses issues in the online frequency domain identification of a flexible two-mass mechanical system with varying dynamics, and a particular attention is paid to detect the changes in the system dynamics. An online identification method is presented that is based on a recursive Kalman filter configured to perform like a discrete Fourier transform (DFT) at a selected set of frequencies. The experimental online identification results are compared with the corresponding values obtained from the offline-identified frequency responses. The results show an acceptable agreement and demonstrate the feasibility of the proposed identification method

General-Purpose and Scalable Internal-Combustion Engine Model for Energy-Efficiency Studies

Hybrid powertrains that combine electric machines and internal-combustion engines offer substantial opportunities to increase the energy efficiency and minimize the exhaust emissions of vehicles and nonroad working machines. Due to the wide range of applications of such powertrains, simulation tools are used to evaluate and compare the energy efficiency of hybrid powertrains for application-specific working cycles in virtual environments. Therefore, the accurate modeling of the powertrain components of a hybrid system is important. This paper presents an agile calculation tool that can generate realistic fuel consumption data of a scalable diesel engine. This method utilizes a simple efficiency model of the combustion and crank train friction model to generate the fuel consumption map in the operating area of a typical diesel engine. The model parameters are calibrated to produce accurate fuel consumption data in the initial phase of system-level simulations. The proposed method is also validated by using three real engine datasets, and the comparison of results is presented

Power balance control and dimensioning of a hybrid off-grid energy system for a Nordic climate townhouse

This paper investigates conversion of a Nordic oil-heated townhouse into carbon-neutral by different energy efficiency (EE) improvements and an off-grid system including solar photovoltaics (PV), wind power, and battery and hydrogen energy storage systems (BESS and HESS). A heat-pump-based heating system including waste heat recovery (WHR) from the HESS and an off-grid electrical system are dimensioned for the building by applying models developed in MATLAB and Microsoft Excel to study the life cycle costs (LCC). The work uses a measured electrical load profile, and the heat generation of the new heating system and the power generation are simulated by commercial software. It is shown that the EE improvements and WHR from the HESS have a positive effect on the dimensioning of the off-grid system, and the LCC can be reduced by up to €2 million. With the EE improvements and WHR, the component dimensioning can be reduced by 22%–41% and 13%–51% on average, respectively. WHR can cover up to 57% of the building's annual heat demand, and full-power dimensioning of the heat pump is not reasonable when WHR is applied. Wind power was found to be very relevant in the Nordic conditions, reducing the LCC by 32%.</p