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The doping level dependence of thermoelectric properties of delafossite CuAlO 2 has been investigated in the constant scattering time (s) approximation, starting from the first principles of electronic structure. In particular, the lattice parameters and the energy band structure were calculated using the total energy plane-wave pseudopotential method. It was found that the lattice parameters of CuAlO 2 are a = 2.802 Å and c = 16.704 Å , and the internal parameter is u = 0.1097. CuAlO 2 has an indirect band gap of 2.17 eV and a direct gap of 3.31 eV. The calculated energy band structures were then used to calculate the electrical transport coefficients of CuAlO 2 . By considering the effects of doping level and temperature, it was found that the Seebeck coefficient S(T) increases with increasing acceptor doping (A d ) level. The values of S(T) in our experiments correspond to an A d level at 0.262 eV, which is identified as the Fermi level of CuAlO 2 . Based on our experimental Seebeck coefficient and the electrical conductivity, the constant relaxation time is estimated to be 1 9 10 À16 s. The power factor is large for a low A d level and increases with temperature. It is suggested that delafossite CuAlO 2 can be considered as a promising thermoelectric oxide material at high doping and high temperature.

An effective model of battery performance is important for battery management systems to control the state of battery and cell balancing. The second-order equivalent circuit model of a lithium-ion battery is studied in the present paper. The identification methods that include the multiple linear regression (MLR), exponential curve fitting (ECF) and Simulink design optimization tool (SDOT), were used to determine the model parameters. The aim of this paper is to compare the validity of the three proposed algorithms, which vary in complexity. The open circuit voltage was measured based on the pulse discharge test. The voltage response was collected for every 10% SOC in the interval between 0–100% SOC. The battery voltages calculated from the estimated parameters under the constant current discharge test and dynamic discharge tests for electric vehicles (ISO and WLTP) were compared to the experimental data. The mean absolute error and root mean square error were calculated to analyze the accuracy of the three proposed estimators. Overall, SDOT provides the best fit with high accuracy, but requires a heavy computation burden. The accuracy of the three methods under the constant current discharge test is high compared to other experiments, due to the nonlinear behavior at a low SOC. For the ISO and WLTP dynamic tests, the errors of MLR are close to that of SDOT, but have less computing time. Therefore, MLR is probably more suitable for EV use than SDOT.

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