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Fuzzy Front End
Published in Ali Jamnia, Introduction to Product Design and Development for Engineers, 2018
An example of a breakthrough product in the automotive industry is a contactless fuel level sensor. In the majority of automobiles, the fuel gauge is a combination of a float, a float arm, and a simple potentiometer. As the fuel level in the tank changes, the float moves up or down, and along with it, the float arm pivots around a fixed point. The movement of the float arm describes an arc. By connecting a circular potentiometer to the center of the rotation, it is possible to measure the change in the resistance as the float arm rotates up and down with changes in the fuel level. By correlating the two, the fuel levels in the tank may be measured. The failure modes of these fuel sensors are either corrosion of the potentiometer or collection of debris and gunk on the resistive track, either preventing arm movement or creating electrical noise and causing inaccurate readings. One solution to remove these failure modes is to remove the need for a resistive circuit as a means of measuring the fuel level. This was achieved by using magnetics and measuring the strength of the magnetic field using a hall-effect sensor (Jamnia and Chen 2007).
Effects of heat load and hypobaric hypoxia on cognitive performance: a combined stressor approach
Published in Ergonomics, 2023
Charelle Bottenheft, Eric L. Groen, Douwe Mol, Pierre J. L. Valk, Mark M. J. Houben, Boris R. M. Kingma, Jan B. F. van Erp
The SYNWIN is also a computer-based task with multiple tasks to be performed simultaneously (Elsmore, 1994). It has been used in studies of human-computer interaction and sustained operations in cockpit setting (Hambrick et al. 2010), and also in hypobaric hypoxia conditions (Beer et al. 2017). It represents different cognitive skills required in complex task situations. The SYNWIN includes four tasks: a simple memory task, an arithmetic computation task, a visual monitoring task, and an auditory monitoring task. Performance measures included a SYNWIN Composite Score and measures determining the accuracy, reliability, and speed of responses for each individual cognitive task. The Composite Score represents performance across all four tasks by including points earned minus penalties for incorrect responses, namely incorrect or missed identification in the memory task, incorrect calculation, allowing the fuel gauge to expire, and auditory false alarms or misses. Performance measures for the visual monitoring task consisted of total earned points and lapse rate (number of time participant allowed gauge to reach zero divided by number of sampling periods). For the auditory monitoring task percentage correct is used as performance measure. The total duration of this task was 10 min.
An Adaptive Algorithm for Battery Charge Monitoring based on Frequency Domain Analysis
Published in IETE Journal of Research, 2021
Poulomi Ganguly, Surajit Chattopadhyay, B.N Biswas
An improved battery management system is of utmost importance to improve the appeal of EVs. Battery aging effect, self-discharging, and effect of overcharging may affect its operation and hence the performance of EV. Despite the various researches that have been carried out regarding battery, further research in this area is required due to the practical repercussions of its operational issue [20]. The battery State-of-charge (SOC) level acts as a fuel gauge indicator of a conventional automobile. Also, the battery operation and SOC level are highly influenced by the dynamic operation of EV. Effective EV battery management system is highly dependent on the proper determination of SOC [21]. Self-discharge or decay of automotive batteries after long-term use for EV has not been considered previously. The current response will vary as the battery deteriorates over time. In this paper, the changing or decreasing battery charge level effect on response profile has been studied through MATLAB Simulink. The changes in response characteristics have been recorded. The data thus recorded has been then analysed in the frequency domain through FFT analysis, and the result as obtained has been demonstrated graphically. The automobile system considered here is a modern conventional oil-based automobile system with an electric starter. Based on the observation obtained here we wish to extend our research into EV and develop a proper reliable monitoring algorithm.
Real-world fuel use and gaseous emission rates for flex fuel vehicles operated on E85 versus gasoline
Published in Journal of the Air & Waste Management Association, 2018
Maryam Delavarrafiee, H. Christopher Frey
Variability in emission rates when comparing vehicles of different manufacturers is because of differences in FFV engine control strategies (Yanowitz et al. 2013). FFV engines have sensors to analyze the fuel mixture and adjust the fuel injection and timing. The sensors can include the fuel gauge, exhaust oxygen sensor, a knock sensor, and a fuel composition sensor in the fuel line, which help to optimize operation for different ranges of fuel oxygen content, energy content, and octane. Different FFV manufacturers developed different engine control strategies to adjust to variation in fuel energy and oxygen content. NOx emission rates are mainly produced during moderate to heavy power demand when combustion temperatures and pressure are high. Without having information regarding those parameters, it is difficult to explain why there are different patterns in difference in emission rates between fuels among VSP modes.