Lastly, a test with several consecutive Federal Urban Driving Schedules (FUDSs) profiles is carried to evaluate the model-based dynamic multi-parameter method for peak power estimation.
A model-based dynamic multi-parameter method for peak power estimation is proposed for batteries and battery management systems (BMSs) used in hybrid electric vehicles (HEVs).
The experimental and simulation results indicate that the model-based dynamic multi-parameter method for peak power estimation can calculate the terminal voltage and the current available power much more reliably and accurately.
Firstly, an enhanced model for the initial SOC (SOC0) estimation based on dynamic multi-parameter method is investigated, because SOC0 plays a key role in calculating real SOC in-time.
A model-based dynamic multi-parameter method for peak power estimation of lithium ion batteries is proposed to calculate the reliable available power in real time, and the design limits such as cell voltage, cell current, cell SoC, cell power are all used as its constraints; more importantly, the relaxation effect also is considered.
We propose a Wide-Field Multi-Parameter FLIM method (WFMP-FLIM) aimed to monitor continuously living cells under minimum light intensity at a given illumination energy dose.
In summary our novel wide-field multi-parameter FLIM method, based on interleaved synchronized laser excitation of multiple fluorophores in combination with TCSPC by a space sensitive photomultiplier provides several advantages compared to current time-domain FLIM systems.
Li, et al [51], presented an adaptive cascaded stochastic resonance method to detect the weak impulsive features submerged in noise; the multi-parameters of this method were optimized by GA synchronously, and results showed that the proposed method was suitable for extracting the weak impact features of a gearbox.
The individual-tree model was constrained by diameter-class attributes (equations 15 16 of Table 1) by use of the multi-response parameter estimation method (Zhang et al. [1997], Bates and Watts [1987], [1988]).
Multi-parameter evidence synthesis methods were applied to combine all available relevant data sources - both direct and indirect - that inform the epidemiological parameters of interest.
Finally, the optimal choice of the three methods for simultaneously estimating multi-parameters of temperature-dependent thermal conductivities of the Inconel is suggested, that is accurate, robust, convergence stable and the most efficient.
