This paper gives a comprehensive review of advanced cooling schemes and their applications to the permanent magnet synchronous motors (PMSMs), as well as investigating the electrical motor’s topologies its thermal design issues, materials and performances. Particularly, the electromagnetic and electric performances, machine sizing, together with the structural design, are given. In addition, the work addresses the motor’s material design and properties along with its insulation performance, which is the main goal of optimization. Mainly, thermal mapping with analysis is provided according to the different cooling methods, including air-cooling, water-cooling, oil-cooling, heat-pipe-cooling, potting silicon gelatin cooling, and as well as cooling strategies for tubes and microchannels. The most common special features and demands of the PMSMs are described in the appearance of the motor’s failures caused by uncontrolled temperature rise. In addition, heat sources and energy losses, including copper loss, core loss versus motor speed, and output power, are analyzed. The review of the proposed cooling methods that will achieve the required heat transfer of the PMSM is presented with numerical simulations and measurements data. A review of numerical methods and results, including the finite element methods (FEM), such as the Ansys CFD software, to obtain a high-accuracy thermal mapping model of the PMSM system is given. The revived methods and design requirements due to PMSM temperature profile and cooling flow at different rotor speeds and torque loads are investigated. Finally, the motor design recommendations, including the newly developed cooling solutions, which enable it to effectively redistribute the temperature and heat transfer, increasing the efficiency of the PMSM machine, are laid out.

Systems for determining the position of objects inside buildings have a wide range of applications, such as the surveillance of people’s movements in hospitals, and of goods or mobile robots in warehouse spaces or production halls. Hence, there is a need for the development of methods that could be applied for those purposes. This paper presents the results of research on an experimental system for localizing people being evacuated from a building. The proposed solution was designed as a part of the building evacuation management system. The method used for finding location belongs to the class of proximity-type methods and is based on Received Signal Strength Indicator (RSSI) information of Bluetooth Low-Energy (BLE) devices. The devices used to build the system (BLE receivers) and the evacuee’s wristband (BLE transmitters) are low-budget electronic modules. The paper presents preliminary research and the process of selecting data processing methods, as well as the results of tests of the experimental network created for the evacuation system. The results of measurements and statistical analyses of the properties of the RSSI parameter of the BLE signal transmission between the modules used in the designed system are presented. In addition, the results of RSSI measurements and the analyses of RSSI recorded under varying environmental conditions in the building are presented. The choice of the data processing method and its parameters was made with the use of the determined probabilities of the nearest locator node detection. Finally, the performance of the experimental installation of the evacuee tracking system was tested and the effectiveness of the proximity method was evaluated. The experimental tests aimed to analyze the detection range and the impact of shading. They also allowed for determining the mean error and for estimating the maximum position determination error. It should be emphasized that the proposed position estimation method has a very low computational load, allowing the implementation of an extensive real-time system on a typical personal computer. Although the proposed system should be classified as a coarse positioning system, its features such as low cost, simplicity, flexibility, the use of commonly available components and low requirements for computational load make it attractive. Such a system is directly transferable to other applications in, for example, Industry 4.0.

Methods for estimating a car’s length are presented in this paper, as well as the results achieved by using a self-designed system equipped with two anisotropic magneto-resistive (AMR) sensors, which were placed on a road lane. The purpose of the research was to compare the lengths of mid-size cars, i.e., family cars (hatchbacks), saloons (sedans), station wagons and SUVs. Four methods were used in the research: a simple threshold based method, a threshold method based on moving average and standard deviation, a two-extreme-peak detection method and a method based on the amplitude and time normalization using linear extrapolation (or interpolation). The results were achieved by analyzing changes in the magnitude and in the absolute z-component of the magnetic field as well. The tests, which were performed in four different Earth directions, show differences in the values of estimated lengths. The magnitude-based results in the case when cars drove from the South to the North direction were even up to 1.2 m higher than the other results achieved using the threshold methods. Smaller differences in lengths were observed when the distances were measured between two extreme peaks in the car magnetic signatures. The results were summarized in tables and the errors of estimated lengths were presented. The maximal errors, related to real lengths, were up to 22%.

The proper operation of computing resources in a microprocessor-embedded system plays a key role in reducing computing time. Processing the variable amount of collected data in real-time improves the performance of a microprocessor-embedded system. In this regard, a vehicle’s speed measurement system is no exception. The computing time for evaluating any speed value is expected to be reduced as much as possible. Four computational methods, including cross-correlation, are discussed. An exemplary pair of recorded signals presenting the change in magnetic field magnitude is analyzed. The sample delay values are compared. The results of the evaluated speed and the execution time of the program code are presented for each method based on a dataset of 200 randomly driven vehicles. The results of the performed tests confirm that the cross-correlation-based methods are not always reliable in situations when the sample size is small, i.e., it is a segment of the impulse response caused by a driving vehicle.

In this article, we have reviewed the available positioning, localization and navigation techniques for mobile robots. Different localization techniques based on diverse technologies are compared with one another, along with diverse algorithms and techniques for analyzing this information. The article highlights algorithms based on odometry, triangulation, visual analysis, and marker detection. The analysis included global, local, and personal location. One acquires knowledge on which method is suitable for indoor use and which for outdoor use, as well as the appropriate environmental conditions for each. The accuracy of the individual methods was compared with that of integrated systems consisting of several methods. For practical knowledge, it is possible to determine whether a particular method is cost-effective for a particular solution and to compare the expenses involved.