In order to improve the convergence time and stabilization accuracy of the real-time state estimation of the power batteries for electric vehicles, a fuzzy unscented Kalman filtering algorithm (F-UKF) of a new type is proposed in this paper, with an improved second-order resistor-capacitor (RC) equivalent circuit model established and an online parameter identification used by Bayes. Ohmic resistance is treated as a battery state of health (SOH) characteristic parameter, F-UKF algorithms are used for the joint estimation of battery state of charge (SOC) and SOH. The experimental data obtained from the ITS5300-based battery test platform are adopted for the simulation verification under discharge conditions with constant-current pulses and urban dynamometer driving schedule (UDDS) conditions in the MATLAB environment. The experimental results show that the F-UKF algorithm is insensitive to the initial value of the SOC under discharge conditions with constant-current pulses, and the SOC and SOH estimation accuracy under UDDS conditions reaches 1.76% and 1.61%, respectively, with the corresponding convergence time of 120 and 140 s, which proves the superiority of the joint estimation algorithm.

To ensure effective heat recovery of thermoelectric generators, a cooling system is necessary to maintain the working temperature difference of the thermoelectric couples, which decreases continuously due to thermal diffusion. In order to evaluate and improve the thermoelectric performance of a concentric annular thermoelectric generator under various cooling methods, a comprehensive numerical model of the thermo-fluid-electric multi-physics field for an annular thermoelectric generator with a concentric annular heat exchanger was developed using the finite-element method. The effects of four cooling methods and different exhaust parameters on the thermoelectric performance were investigated. The results show that, in comparison to the cocurrent cooling pattern, the countercurrent cooling pattern effectively reduces temperature distribution non-uniformity and hence increases the maximum output power; however, it requires more thermoelectric semiconductor materials. Furthermore, when using the cocurrent air-cooling method, high exhaust temperatures may result in lower output power; high exhaust mass flow rates result in high exhaust resistance and reduce system net power. The maximum net power output P_net = 432.42 W was obtained using the countercurrent water-cooling, corresponding to an optimal thermoelectric semiconductor volume of 9.06 × 10⁻⁴ m³; when compared to cocurrent water-cooling, the maximum net power increased by 8.9%, but the optimal thermoelectric semiconductor volume increased by 21.4%.

The output characteristics of the Proton-Exchange Membrane Fuel Cells (PEMFCs) are affected by multiple factors, but quantitatively describing the relationships is challenging. In this paper, a semi-empirical dynamic model of PEMFC is established firstly. The influence of a single factor on the output characteristics of PEMFC is analyzed longitudinally. Then, a derivative significance weight analysis based on support vector regression (SVR-DSWA) algorithm is proposed to analyze the influence weights of multi-factors on the output characteristics, and the optimal parameters combinations in different current density regions are obtained by maximizing the output voltage values based on formulated SVR model. The Root-Mean-Square Error (RMSE) of output voltage prediction results based on the SVR algorithm is less than 0.0458, and the accuracy of weight analysis results by using the SVR-DSWA algorithm and the optimal parameters combinations analysis method are verified by 4-factor 3-level orthogonal experiments in low, medium, and high current density regions. The SVR-DSWA algorithm and optimal parameters combinations analysis method can replace the orthogonal experiment to analyze the influence weights and optimal combinations of input factors on the output characteristics within the full current density range rapidly, and has much higher efficiency than the orthogonal experiment. The analysis results can provide theoretical support for improving fuel cell performance and formulating a control strategy.