Reliable estimation of longitudinal force and sideslip angle is essential for vehicle stability and active safety control. This paper presents a novel longitudinal force and sideslip angle estimation method for four-wheel independent-drive electric vehicles in which the cascaded multi-Kalman filters are applied. Also, a modified tire model is proposed to improve the accuracy and reliability of sideslip angle estimation. In the design of longitudinal force observer, considering that the longitudinal force is the unknown input of the electric driving wheel model, an expanded electric driving wheel model is presented and the longitudinal force is obtained by a strong tracking filter. Based on the longitudinal force observer, taking into consideration uncertain interferences of the vehicle dynamic model, a sideslip angle estimation method is designed using the robust Kalman filter and a novel modified tire model is proposed to correct the original tire model using the estimation results of longitudinal tire forces. Simulations and experiments were carried out, and effectiveness of the proposed estimation method was verified.

This paper presents a low-cost and smart measurement system to acquire and analyze mechanical motion parameters. The measurement system integrates several measuring nodes that include one or more triaxial accelerometers, a temperature sensor, a data acquisition unit and a wireless communication unit. Particular attention was dedicated to measurement system accuracy and compensation of measurement errors caused by power supply voltage variations, by temperature variations and by accelerometers’ misalignments. Mathematical relationships for error compensation were derived and software routines for measurement system configuration, data acquisition, data processing, and self-testing purposes were developed. The paper includes several simulation and experimental results obtained from an assembled prototype based on a crank-piston mechanism

The paper describes studies on the influence of humidity on the electrical resistance of a textile sensor made of carbon fibres. The concept of the sensor refers to externally bonded fibre reinforcement commonly used for strengthening of structures, however the zig-zag arrangement of carbon fibre tow allows for measuring its strain. The sensor tests showed its high sensitivity to the temperature and humidity changes which unfavourably affects the readings and their interpretation. The influence of these factors must be compensated. Due to the size of the sensor, there is not possible electrical compensation by the combining of “dummy” sensors into the half or full Wheatstone bridge circuit. Only mathematical compensation based on known humidity resistance functions is possible. The described research is the first step to develop such relations. The tests were carried out at temperatures of 10°C, 20°C, 30°C and humidity in the range of 30-90%.

When machine tool spindles are running at a high rotation speed, thermal deformation will be introduced due to the generation of large amounts of heat, and machining accuracy will be influenced as a result, which is a generalized issue in numerous industries. In this paper, a new approach based on machine vision is presented for measurements of spindle thermal error. The measuring system is composed of a Complementary Metal-Oxide-Semiconductor (CMOS) camera, a backlight source and a PC. Images are captured at different rotation angles during end milling process. Meanwhile, the Canny edge detection and Gaussian sub-pixel fitting methods are applied to obtain the bottom edge of the end mill which is then used to calculate the lowest point coordinate of the tool. Finally, thermal extension of the spindle is obtained according to the change of the lowest point at different time steps of the machining process. This method is validated through comparison with experimental results from capacitive displacement sensors. Moreover, spindle thermal extension during the processing can be precisely measured and used for compensation in order to improve machining accuracy through the proposed method.