Kalman Filter 알고리즘을 활용한 제설제의 융빙 성능 평가에 관한 연구

PURPOSES: The intensiveness of highway management has increased owing to the growth in the number of vehicles and the rapid climate change. The disadvantages produced by these factors can affect management time and cost. Serious traffic accidents and traffic jam may be experienced when snow fall accumulates on highway surfaces and the friction between tires and pavements is lower than that in the general state, in a non-management condition. Such conditions need intensive management. In this regard, one of the spread methods used for the melting material is pre-wetted salt (PWS), which is the frequently used method in South Korea. In the PWS method, the solid material with CaCl2 is mixed with water in 30% concentration and then finally mixed with NaCl before application to pavements. The chloride-type melting material not only is cheaper, but also has a high melting property than the others. It can shorten the pavement or structure life by deterioration and corrosion. This melting material can affect the flora near the highways; hence, an eco-friendly de-icing agent must be utilized considering the environmental effect.METHODS : The Kalman filter algorithm (KFA) was utilized herein to develop optimization models using the performed test data. The KFA, which was developed from recursive filter algorithms, such as the low- and high-pass filters, applies a weighting filter to the Kalman filter. The algorithm has the property of utilizing the filter and updated estimations. In this regard, melting tests were performed for the real applicative utilization of de-icing agents. The KFA was also applied to reduce the error rates and optimize the relationships between the test data and the predictions.RESULTS: Comparing the measurements performed, the error was reduced by 1.69 g when the KFA was applied. Moreover, the error can be optimized to approximately 91.4% compared to the test errors. The prediction data had over 85% tendency in the test measurement, showing that the KFA application can reduce the error and increase the tendency. By comparison, the agent with CaCl2 showed the best ice melting performance within 10 min without surface temperature. However, the PWS with a 25% concentration indicated the best water melting performance from start to end of the test time, implying that this is a powerful agent in terms of performance.CONCLUSIONS : The melting test is an artificial test method; therefore, it can generate a huge error from the test. The error and the tendency can be controlled by tracking the measurement error and the white noise matrix using the KFA. A further research will be performed to track the measurement error and the white noise matrix. Other optimization methods will also be applied to reduce the experimental error.