Automobile anti-lock braking system (ABS) is an important component of vehicle active safety control system and is widely used in various automobiles. In the car braking process, the car equipped with ABS can effectiv...
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Automobile anti-lock braking system (ABS) is an important component of vehicle active safety control system and is widely used in various automobiles. In the car braking process, the car equipped with ABS can effectively shorten the braking distance, and avoid vehicle side-slip, etc., ensuring the braking performance and driving safety of the vehicle. In order to further improve the performance and robustness of automobile ABS, a robust ABS control method based on road recognition is proposed for the current ABS control method. Based on the fuzzylogic control method, the road surface adhesion coefficient is estimated to realize the road surface recognition, and the optimal slip rate is dynamically obtained. According to the slip rate, a robust controller of ABS is designed. The simulation results show that the robust controller of ABS has good control effect and robustness and can estimate the road adhesion coefficient in real time. (C) 2022 Jordan Journal of Mechanical and Industrial Engineering. All rights reserved
Induction Motors (IMs) have multiple advantages, as they are robust and easy to maintain. A small fault in a single rotor bar could cause the break of this bar, subsequently breaking a large adjacent bar number becaus...
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Induction Motors (IMs) have multiple advantages, as they are robust and easy to maintain. A small fault in a single rotor bar could cause the break of this bar, subsequently breaking a large adjacent bar number because of the oscillations created by the unbalance of the rotor. For this reason, early detection of any small failure is recommended to remove some posterior damage and the maintenance expenses. This work proposes a new and original method that uses the cyclostationnarity of the electrical signal instead of the vibratory signal to detect the incipient failure. The experimental data has been manipulated. The results prove that this new designed strategy can identify and classify the level of cracking that occurs in a single rotor bar, even under various loads.
An early-warning and explosion-proof monitoring system for coal mine environment is designed based on Zig Bee, in view of the underground special environment. The underground system, with CC2530 + CC2401 chip as the c...
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An early-warning and explosion-proof monitoring system for coal mine environment is designed based on Zig Bee, in view of the underground special environment. The underground system, with CC2530 + CC2401 chip as the core of ZigB ee node, realizes communication with upper computer through CAN bus by the central controller. Upper computer uses the Labview software to program and realize real-time display of the coal mine parameters including CH, CO, O concentration, temperature and humidity and personnel coordinates. The early warning technology based on fuzzy logic algorithm, explosion-proof technology based on physical isolation are adopted to this system. A kind of RSSI weighted centroid algorithm mixed with LQI was put forward. Experiment proved that this system runs stably, improving the personnel positioning accuracy and has a good prospect of application.
Hybrid electric vehicles (HEV) can provide a same power as gasoline and diesel-powered vehicles while also reducing fuel consumption by 40-50%. However, due to a complex system of HEV, the power control strategies are...
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Hybrid electric vehicles (HEV) can provide a same power as gasoline and diesel-powered vehicles while also reducing fuel consumption by 40-50%. However, due to a complex system of HEV, the power control strategies are used to improve the work efficiency, fuel economy and to reduce exhaust emissions. In the present work, four parameters are studied with the main focus on the optimization of power system of a parallel hybrid vehicle. These parameters are the influence of fuzzy logic algorithm on hybrid electric vehicle power train that is acceleration performance, climbing performance, engine efficiency and exhaust gas emissions. First, the vehicle's power train is optimized using the Advanced Vehicle Simulator (ADVISOR). Secondly, by ensuring acceleration and climbing performance, the vehicle manufacturing cost is reduced by reducing the weight of the vehicle. Thirdly, two driving road test conditions, Extra-Urban Driving Cycle (EUDC) and Urban Dynamometer Driving Schedule (UDDS) are used to enhance the fuel consumption efficiency of the vehicle. Using a fuzzy logic algorithm for random operations, the operating range of an internal combustion engine is controlled as much as possible in the most efficient range. Through the control of 121 different algorithms, the operating efficiency of the powertrain is optimized to reduce exhaust emissions and improve fuel efficiency. The results showed that the proposed strategy can reduce fuel consumption by 5%, CO by 50% and improved the operating efficiency of engine by 15%. Not only this control strategy optimizes the efficiency of powertrain, but also the efficiency of the internal combustion engine. Moreover, the motor and battery pack itself can be optimized. These hybrid vehicles can minimize the fuel demand and are the best substitute for the classic internal combustion engines.
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