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The pressure in the wheel cylinder plays an important role in the anti-lock braking system, but direct measurement usually needs expensive sensors. Therefore, estimation of the pressure in the wheel cylinder is of great significance to optimize the algorithm of the anti-lock braking system. There are two commonly used estimation methods: one is based on the hydraulic model, and the other is based on the equation for the tyre dynamics. Both of these, however, suffer from inadequacies. The former method is sensitive to the accuracy of the model in practical applications, and an accumulated error appears if some parameters of the process are not sufficiently accurate. In the latter method the pressure in the wheel cylinder is calculated for each cycle but, when the vehicle is running, the fluctuations in the deceleration are relatively large. To estimate the pressure more accurately, a novel method is proposed in this paper, which combines these two methods on the basis of the extended Kalman filter. The method can compensate for the inadequacies of the two methods mentioned above by using the variation in the wheel speed as the observation variable to modify the hydraulic model. It can decrease its sensitivity to the accuracy of the hydraulic model and improve the accuracy of the estimated magnitude of the pressure. The estimated results are compared with the real values which are obtained by using a pressure sensor on a typical low-friction road and on an asphalt road; in addition, the effectiveness of the novel method is validated by hardware-in-the-loop tests and vehicle tests. The results show that the proposed method can provide an accurate estimation of the pressure in the wheel cylinder during hydraulic control of the anti-lock braking system or any other brake control system. [ABSTRACT FROM AUTHOR]

As is known, estimation of the dynamic states of a vehicle plays an important role in safety control, but it is difficult to obtain the vehicle states accurately without expensive measurement instruments because of the non-linear and huge hysteretic characteristics. Nowadays, many methods have been adopted to solve this problem, the results of which are not ideal because it is assumed that the key parameters are constant, in particular in severe manoeuvres. This paper develops a novel estimation method for the vehicle states using the extended Kalman filter with a fusion algorithm. First, the optimal key parameters (the equivalent roll stiffness and the equivalent roll damping) are identified by genetic algorithms using the data from the relationship between the key parameters and the vehicle real-time states. Then, a novel non-linear observer for the side-slip angle and the roll angle is established on the basis of a four-degree-of-freedom vehicle model by utilizing the identified key parameters and the sensors mounted on normal vehicles. The performance of the observer is investigated using both simulations and real-vehicle experiments. The results demonstrate the reasonable accuracy of the estimation method proposed in this paper. [ABSTRACT FROM AUTHOR]

Apple trees encounter problems such as stressful environments and pathogen infection throughout their entire growth and development, which limits apple production. WRKY transcription factors play a vital role in the defense against pathogens, but their functions in apple trees need to be further explored. In this study, the MdWRKY61 gene, which encodes the WRKY61 protein of the WRKY group II family, was isolated from GL-3 apple. Tobacco subcellular localization experiments showed that the MdWRKY61 protein is located in the nucleus. Quantitative reverse transcription PCR analysis suggested that MdWRKY61 is highly expressed in the roots and fruits of apples and is rapidly induced in response to salicylic acid, jasmonic acid and Colletotrichum siamense. We obtained MdWRKY61 overexpression lines through Agrobacterium -mediated stable genetic transformation of apple. Subsequent experiments revealed that overexpression of MdWRKY61 increased the resistance of apple to Colletotrichum siamense and promoted the upregulation of defense-related gene expression. Taken together, our data provide insights that MdWRKY61 plays an important role in apple resistance to fungal disease. • First research on the function of MdWRKY61. • MdWRKY61 was induced by Colletotrichum siamense , SA and JA. • MdWRKY61 can improve the resistance of apples to Colletotrichum siamense. [ABSTRACT FROM AUTHOR]