Abstract: A method for detecting an abnormality of a fluid filter includes: detecting a flow rate of a fluid in the fluid filter; detecting a pressure difference in the fluid filter; constructing an operating model of the fluid filter in accordance with a geometry of the fluid filter, a physical characteristic of the fluid, a porosity of the fluid filter, an impurity density, the flow rate and the pressure difference; obtaining an initial impurity accumulative quantity through the operating model; estimating a time dependent impurity accumulative status through a Kalman filter in accordance with the initial impurity accumulative quantity and the pressure difference; obtaining an impurity accumulative quantity in an estimated time in accordance with the time dependent impurity accumulative status, and then comparing the impurity accumulative quantity with a pre-determined value to determine if the fluid filter operates normally.

Abstract: A method for estimating efficiency of a particulate filter of a vehicle is provided. The method includes: calculating a first estimated value representing an amount of particulate matters (PM) accumulated in the particulate filter; upon determining to perform regeneration of the particulate filter based on the first estimated value, injecting fuel into the particulate filter and combusting the PM; calculating a second estimated value representing an amount of particulate matters accumulated in the particulate filter after the regeneration; and determining whether a PM accumulation condition of the particulate filter requires user attention based on the second estimated value.

Abstract: A method for estimating efficiency of a particulate filter of a vehicle is provided. The method includes: calculating a first estimated value representing an amount of particulate matters (PM) accumulated in the particulate filter; upon determining to perform regeneration of the particulate filter based on the first estimated value, injecting fuel into the particulate filter and combusting the PM; calculating a second estimated value representing an amount of particulate matters accumulated in the particulate filter after the regeneration; and determining whether a PM accumulation condition of the particulate filter requires user attention based on the second estimated value.

Abstract: A method for detecting an abnormality of a fluid filter includes: detecting a flow rate of a fluid in the fluid filter; detecting a pressure difference in the fluid filter; constructing an operating model of the fluid filter in accordance with a geometry of the fluid filter, a physical characteristic of the fluid, a porosity of the fluid filter, an impurity density, the flow rate and the pressure difference; obtaining an initial impurity accumulative quantity through the operating model; estimating a time dependent impurity accumulative status through a Kalman filter in accordance with the initial impurity accumulative quantity and the pressure difference; obtaining an impurity accumulative quantity in an estimated time in accordance with the time dependent impurity accumulative status, and then comparing the impurity accumulative quantity with a pre-determined value to determine if the fluid filter operates normally.

Abstract: A gas cross-sensitivity analysis method is provided. The method includes, an injection frequency signal is generated from a first gas. A second gas sensing signal is captured from a second gas. Then, the second gas sensing signal is converted to a second gas sensing frequency signal by using Fast Fourier Transform. Further, a sensing peak frequency signal is determined from peak frequency of the second gas sensing frequency signal. The injection frequency signal and the sensing peak frequency signal are analyzed. A gas cross-sensitivity effect can be direct interpretation by a singular indication between the injection frequency signal and the sensing peak frequency signal.

Abstract: A gas cross-sensitivity analysis method is provided. The method includes, an injection frequency signal is generated from a first gas. A second gas sensing signal is captured from a second gas. Then, the second gas sensing signal is converted to a second gas sensing frequency signal by using Fast Fourier Transform. Further, a sensing peak frequency signal is determined from peak frequency of the second gas sensing frequency signal. The injection frequency signal and the sensing peak frequency signal are analyzed. A gas cross-sensitivity effect can be direct interpretation by a singular indication between the injection frequency signal and the sensing peak frequency signal.