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The main aim of the study is to get the temperature and backpressure of a car engine exhaust gas which goes through the EGR-cooler. So the internal fluid flow and heat transfer process of the EGR cooler must be studied more clearly, numerical simulations are applied. Based on the strong coupling method, gas-solid-liquid three phases coupling model of the typical heat transfer unit is established. According to the coupling result, the heat flux of the tube's outside surface is gained and then mapped to the inner surface of the cooler's water. The water model is set up based on the separation coupling method. According to the analysis of the calculation, the detailed pressure and temperature distribution of the gas, water and solid are obtained. From the distribution cloud, we know the changes of the parameters along the fluid flows streamline.

Kalman filters (KFs) are effective tools for estimating online state of charge (SOC), and a great variety of studies about different kinds of KFs have been published. However, problems remain in this field. First, the impact of ambient temperature on the internal parameters of equivalent circuit models (ECM) are seldom discussed. Second, comparative studies about different KFs are not fully validated under different conditions. To solve these problems, a modified equivalent circuit model was developed. The model was proposed to serve in ambient temperature and the usage of the total available capacity. Two typical nonlinear KFs, namely, the extended and unscented KFs were applied in SOC estimation. The model parameters were identified by hybrid pulse power characterization tests at 0, 15, 30, 45, and 55 ℃. Meanwhile, the algorithms were validated under self-designed federal urban driving schedule sequence profiles at 0, 10, 20, 30, 40, and 50 ℃ with the same tuning setups. The robustness of the algorithm was also investigated in terms of voltage sensor uncertainty and the initial SOC offset. Results indicated that the proposed model can achieve the minimum mean absolute error and root mean squared error with the unscented KF at all test conditions.

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