## 1 Introduction  
In technical practice, precise liquid level measurement is often necessary [1]. One common method for such measurement is the ultrasonic signal measurement, which has various applications beyond level measurement, including determining the composition of multiphase flow of oil, water, and gas in pipelines [2], monitoring pipeline corrosion in oil and gas [3], measuring the three-phase flow of oil, gas, and water in the oil production and transportation process [4], measuring the density of liquids [5; 6], and determining the concentration of emulsion liquids [7]. The automotive industry deploys a wide range of sensors and sensor systems in its solutions, and one of the purposes is to measure oil levels. In general, for the purpose of liquid level measurement, for example, ultrasonic [8; 9; 10], optical [11; 12; 13], or capacitive [14; 15; 16] principles can be used [17]. However, not all of them are suitable for measuring the oil level as there are constant changes in the oil properties and even the environment of the engine itself [18]. The most commonly used oil level sensors are ultrasonic-based [17] thanks to their lower price and good properties for measuring an oil level. There is pressure from the automotive industry to keep costs as low as possible, but this is not compatible with the high accuracy and quality of the sensors used. This study focuses specifically on improving the accuracy of oil level measurement with an ultrasonic level sensor that gives measurement range and temperature range, where the design and materials used in the sensor can affect the signal generated and analyzed [19; 20]. A major challenge in using ultrasonic signal measurement for oil level measurement is the significant dependence of the ultrasonic signal response on temperature and viscosity [19; 21; 22; 23]) describing physical phenomena and possible elimination-type methods. Results of measurements of this study are based on an MCU Renesas RL78/F13 processor, which controls the ultrasonic measurement with the implemented algorithm of ultrasonic signal generation and processing, while a comparison of other processors for controlling the measurement processes can be found in a separate study by [PERSON] et al. [24]. Unlike existing and described methods, the novelty of this work lies in the use of statistical methods of ANOVA and regression analysis to improve the accuracy of oil level measurements without changing the hardware configuration. By analyzing and correcting ultrasonic signal measurements, this study provides a precise and computationally validated method of level detection [21]. The content of this study is divided into two parts. The first part focuses on determining the dependence of the amplitude value of the measured signal on the reference value and temperature level for three different engine oil levels. The second part presents the objective of the study, which is to determine the time coefficient \(\Delta\)t (\(\mu\)s), defined as the difference between the _PulseStart_ value (\(\mu\)s) and the _AmplitudeStart_ value (\(\mu\)s), where _AmplitudeStart_ can be described as the beginning of the signal envelope when the threshold value of the received signal is exceeded. The sensor under test is controlled by a processor with an implemented experimental electrical circuit, which is described in the text by the circuit's broken-down functional elements. The experimental workstation allows the level and temperature of the engine oil to be fixed, enabling precise measurement and analysis of parameter dependencies. The synthetic engine oil used in the research study is Shell Helix Ultra Professional AF 5W-30 with given physical parameters that are important for the definition of acoustic properties.