The variation of mutual inductance and load parameters will affect the transmission power and efficiency of the inductive power transfer (IPT) system. The identification of mutual inductance and load parameters is an essential part of establishing a stable and reliable IPT system. This paper presents a joint identification method of load and mutual inductance for LCC-S IPT system, which does not require the establishment of primary and secondary communication and related control. Firstly, the resistance-inductance characteristics of the equivalent load of the rectifier are analyzed by simulation, and then the rectifier and system load are equivalent to the circuit model of resistance and inductance in series. Secondly, the characteristics of the reflected impedance are analyzed, and the functional relationship between the transmitter impedance and the rectifier impedance is established by using the ratio of the real part to the imaginary part of the reflected impedance, which realizes the decoupling of the load and the mutual inductance. Thirdly, the functional relationship between the equivalent impedance of the rectifier and the load resistance of the system is obtained by data fitting. Then, the equations of the above two functional relationships are combined. By measuring the voltage of the parallel compensation capacitor at the transmitting side, the current of the transmitting coil and the phase difference between the two, the battery load can be solved first, and then the mutual inductance can be calculated, so that the high-precision identification of the load and mutual inductance can be realized. Finally, an experimental platform of LCC-S IPT system is built for experimental verification. The experimental results show that the maximum identification errors of mutual inductance and load are 5.20 % and 5.53 %, respectively, which proves that the proposed identification method can achieve high precision identification.

Ceftiofur (CEF) sodium is a third-generation broad-spectrum cephalosporin commonly used in an extra-label manner in dogs for the treatment of respiratory and urinary system infections. To contribute to the literature supporting CEF use in companion animals, we have developed a compartmental, nonlinear mixed-effects (NLME) model of CEF pharmacokinetics in dogs (PK). We then used the mathematical model to predict (via Monte Carlo simulation) the duration of time for which plasma concentrations of CEF and its pharmacologically active metabolites remained above minimum inhibitory concentrations (respiratory tractEscherichia coli spp). Twelve healthy beagle dogs were administered either 2.2 mg/kg ceftiofur-sodium (CEF-Na) intravenously (I.V) or 2.2 mg/kg CEF-Na subcutaneously (S.C). Plasma samples were collected over a period of 72 hours post-administration. To produce a measurement of total CEF, both CEF and CEF metabolites were derivatized into desfuroylceftiofur acetamide (DCA) before analysis by UPLC-MS/MS. No adverse effects were reported after I.V or S.C dosing. The NLME PK models were parameterized using the stochastic approximation expectation maximization algorithm as implemented in Monolix 2018R2. A two-compartment mamillary model with first-order elimination and first-order S.C absorption best described the available kinetic data. Final parameter estimates indicate that CEF has a low systemic clearance (0.25 L/h/kg) associated with a low global extraction ratio E = 0.02) and a moderate volume of distribution (2.97 L/kg) in dogs. The absolute bioavailability after S.C administration was high (93.7%). Gender was determined to be a significant covariate in explaining the variability of S.C absorption. Our simulations predicted that a dose of 2.2 mg/kg CEF-Na S.C would produce median plasma concentrations of CEF of at least 0.5 µg/mL (MIC₅₀) for approximately 30 hours.