Overview: This article talks about how important radar sensors are in electric vehicles, including how they work, the different kinds of radar available, what they are used for, and the problems of making things more automated. Helping the human driver in tricky traffic situations and giving some or all of the driving tasks to automatic systems makes traffic safer, more efficient, smoother, and more comfortable. The advancement of sensors, decision algorithms, and intervention components is made possible by semiconductor and information technology developments. What is the role of radar in autonomous driving?Sensors such as lidar, millimeter-wave radar, cameras, ultrasonic radar, and inertial navigation systems are used by autonomous driving to understand its surroundings, as illustrated in Fig. 1. Radar operates in a significantly wider detection range and can function in all weather conditions. Radar has become an important sensor in the autonomous driving of electric vehicles due to developments in full polarization technologies and greater resolution.Fig. 1 Sensors in Autonomous Driving Source: MDPI Working Mechanism of RadarBased on working mechanisms, the radar system can be divided into three modules, as illustrated in Fig. 2.Radar functional moduleRadar algorithm moduleEcho moduleFig. 2 Working Mechanism of Radar Source: MDPI Radar Functional ModuleIt generates radar signals and manages their transmission, reception, and processing. It analyses intermediate frequency signals that carry information about detected targets. The radar functional module comprises two submodules,TransmitterReceiver As shown in Fig. 2, various steps involved in the working of the radar in these two submodules are discussed below 1. TransmitterGenerator: It starts the process and sets the fundamental parameters of the radar waveform. This includes important details like pulse width, frequency, and repeat rate to determine how well the radar works. Voltage-controlled oscillator (VCO) and phase-locked loop (PLL): It produces a modulated pulse. The VCO creates the carrier frequency, and the PLL keeps the frequency stable and precisely controls the modulation process. Frequency multiplier and Power divider: The frequency multiplier increases the signal to the desired transmission frequency, while the power divider splits the signal for various processing needs. This stage effectively prepares the signal for final amplification. Power amplifier: It substantially amplifies the signal's strength to achieve the power levels necessary for effective radar transmission. It is important to determine the radar's effective range and detection capabilities. Transmitting antenna: The transmitting antenna converts the electrical signal into electromagnetic waves propagating through space. The antenna's design characteristics, such as gain and beam width, significantly influence the radar's directional properties and overall performance. 2. ReceiverReceiving antenna: It captures the echo signals that have reflected off-targets and begins the receiving process. The antenna's design characteristics are important for maximizing the reception of these often-weak return signals. Low noise amplifier: It provides initial amplification of the received signals. This component is specifically engineered to minimize the introduction of additional noise while increasing signal strength. Filter: It gets rid of any unwanted high-frequency interference. This screening step is necessary to raise the signal-to-noise ratio and make sure that the next steps focus on the important echo data. Analog to digital converter: This component samples the filtered analog signal and converts it into a digital format that modern computing systems can process. The converted signal is called the raw data containing the target information. Radar Algorithm ModuleIt recognizes the targets and extracts their motion parameters by analyzing digital signals that carry target information via various steps explained below. Three-Dimensional Fast Fourier Transform (3D-FFT): Radar digital signal undergoes 3D-FFT processing, extracting range, velocity, and angle information. This processing generates a range-angle map (information on range and angle) and a range-doppler map (information on range and velocity). Contrast false alarm rate (CFAR): The detection threshold of the CFAR algorithm changes dynamically based on the surroundings. This makes it possible to identify the difference between real targets and background noise. Cluster: It aggregates the identified target points into meaningful groups. This stage is particularly important for complex scenarios where multiple radar returns might represent different aspects of the same target. Target tracking: It continuously monitors detected targets, maintaining detailed records of their parameters such as target intensity, range angle, and velocity. Echo ModuleThe radar echo module is important for processing reflected radio waves. It performs several key functions, which includeDetermines object properties like distance, velocity, and direction.Captures radio waves reflected from objects.Analyzes signal characteristics. Distinct Advantage of Radar Sensors Used in Electric VehiclesRadar with different operating frequencies, as shown in Fig. 3, offers distinctive advantages in electric vehicles described below. Banner engineering offers a variety of radar sensors that can be implemented in electric vehicles.Fig. 3 Radars operating in different frequencies Source: Banner Engineering Radar Operating in Lower FrequencyThe QT50R's (Fig. 4) wide beam pattern (90 x 76 degrees) and robust performance in various weather conditions make it ideal for blind spot detection and parking assistance in EVs. Its low frequency of 24 GHz provides reliable detection even in adverse weather, enhancing safety during precipitation or fog. The multiple sensing ranges (3.5, 12, 24 m) allow for tiered warning systems as objects approach the vehicle.Fig. 4 QT50R Radar Sensor Source: Banner Engineering The sensor's simple DIP configuration and wide coverage area make it effective for large-scale parking lot monitoring, helping drivers locate available charging spots. Its multiple detection zones can differentiate between occupied and vacant spaces. Its’ rugged IP67 housing is suitable for harsh environments like wind, fog, snow, or rain. Radar Operating in High-FrequencyThe T30R's (Fig. 5) high frequency (122 GHz) and superior accuracy make it suitable for precise distance measurements in adaptive cruise control and emergency braking systems. Its narrow beam patterns (15 x 15 or 45 x 45 degrees) enable precise object detection and tracking, which is essential for highway driving and maintaining safe distances from other vehicles.Fig. 5 T30R Radar Sensor Source: Banner Engineering The T30R's high sensitivity can enable precise vehicle classification and positioning guidance, which is particularly useful in automated parking systems and premium charging locations where exact positioning is crucial. Radar Operating in Medium FrequencyK50R, as shown in Fig. 6, operates with a medium frequency range of 60 GHz, generates wavelength to detect objects up to 0.1 to 5 meters, and has a wide-angle beam. These sensors are commonly employed indoors and outdoors in applications like obstacle detection, monitoring parking bay occupancy, correcting vehicle positioning, etc.Fig. 6 K50R Series Radar Sensors Source: Banner Engineering The sensor’s moderate range (5 m) and balanced performance characteristics make it well-suited for EV charging station applications. Its dual configurable zones can help manage vehicle positioning at charging stations, ensuring optimal alignment between the vehicle and charging equipment. The moderate weather performance is sufficient for covered charging stations while maintaining cost-effectiveness. Rapid market penetration is expected because of the advantages of automated driving systems, and there is a high degree of technological advancement needed to implement them. Even though radar sensors in electric vehicles provide many advantages, higher-level automation has not yet been attained. One of the primary reasons for this challenge is that high-level safety validation is required to demonstrate functional safety to the customer. Automotive manufacturers must guarantee that automated driving functions are safer than human drivers. Sensor models for vehicle development are difficult to develop due to the intricate high-frequency mechanics of radars. Researchers are concentrating on novel modeling methodologies for automotive radar sensors. Summarizing the Key PointsRadar sensors play an important role in electric vehicles, enhancing safety and automation by providing accurate detection of surrounding objects in various weather conditions and environments.Different types of radar sensors operating at high, low, and mid-frequency are available for specific applications like collision avoidance, parking assistance, and distance control.The advancement of radar technology is essential for achieving higher levels of vehicle automation, which requires safety validation and testing to ensure reliability and performance. ReferenceMagosi, Z. F., Li, H., Rosenberger, P., Wan, L., & Eichberger, A. (2022). A Survey on Modelling of Automotive Radar Sensors for Virtual Test and Validation of Automated Driving. Sensors, 22(15), 5693. https://doi.org/10.3390/s22155693Huang, K., Ding, J., & Deng, W. (2024). An Overview of Millimeter-Wave Radar Modeling Methods for Autonomous Driving Simulation Applications. Sensors, 24(11), 3310. https://doi.org/10.3390/s24113310Magosi, Z. F., & Eichberger, A. (2023). A Novel Approach for Simulation of Automotive Radar Sensors Designed for Systematic Support of Vehicle Development. Sensors, 23(6), 3227. https://doi.org/10.3390/s23063227BannerEngineering-https://info.bannerengineering.com/cs/groups/public/documents/literature/b_51173014.pdf

Overview: This article provides an overview of neural networks, detailing their structure, types, and applications in various fields. It also addresses neural networks' challenges in enhancing their effectiveness in decision-making tasks. Neural networks are a fundamental component of modern artificial intelligence (AI) systems. Neural network-based deep learning methods have attracted much attention from academia and business in the last ten years. Unlike conventional machine learning models, neural networks are far more expressive and flexible when dealing with complicated data input. What are neural networks?Neural networks are computing models that draw inspiration from the human brain, found by Warren McCulloch and Walter Pitts. Neural networks are a potent class of machine-learning algorithms that have found extensive use in decision-making applications. These networks acquire data and train themselves to recognize relationships between vast amounts of data, making them ideal for tasks involving pattern recognition, classification, and prediction. Key Components of Neural NetworkThey comprise interconnected neurons arranged in layers that learn and replicate intricate relationships between inputs and outputs. A neuron receives input, performs mathematical computation, and generates an output transmitted to neurons in subsequent layers. The three main types of layers, as shown in Fig. 1, areInput layer: Acquires the inputOutput layer: Predict the final resultHidden layers: Completes the majority of the network's computations Fig. 1 Layers of neural network. Source: MDPI Working of Neural NetworksNeural networks are systems of interconnected nodes, or artificial neurons that communicate with each other to analyze and process intricate data patterns via various key steps, as shown in Fig. 2.In the first layer, each neuron receives data as input. The neurons of one layer are connected to those of the other through channels.Weight is a numerical value that is assigned to each channel. Inputs are multiplied by their respective weights, and their sum is supplied as input to the neuron in the hidden layer.Each neuron in the hidden layer is associated with a numerical value called the bias, which is added to the input sum.A threshold function known as an activation function is then applied to this value. Activation functions are essential to neural networks because they introduce non-linearity and allow the network to learn intricate patterns.An activated neuron sends information through the channels to the subsequent layer.The procedure is repeated until the output is obtained. This method of data transmission across a network is known as forward propagation.Fig. 2 Key steps in working of neural networks. Source: MDPI Backpropagation is an additional ML technique that calculates the error for neurons in the final layer and propagates it backward to the preceding layers. It calculates the difference between the expected and actual output. In the event of an error, it is backward-passed via the network. The defect is minimized by updating and adjusting the weight. This efficient algorithm has been extensively employed in research. Neural networks' main advantage is their capacity to generalize and learn from large datasets. The network modifies its internal parameters, or weights, throughout the training phase to reduce the difference between the network's predictions and the actual outputs in the training data. After being trained, neural networks can be utilized for decision-making purposes. It can recognize patterns and conclude training, which qualifies them for use in classification, regression, and pattern recognition applications. Neural Networks TypesDifferent neural network topologies are used in various decision-making applications, as shown in Fig. 3  Fig. 3 Different neural network topologies used in various decision-making situations. Source: MDPIFeedforward neural network (FNN): It is one of the most basic types of neural network in which the information moves unidirectionally from the input to the output layer. It is employed in classification, regression, and pattern recognition applications.Convolutional neural networks (CNNs): Also known as braided networks, they are frequently employed for image and video analysis, including classification, object detection, and segmentation, because they enable the recording of spatial correlations.Recurrent Neural Networks (RNNs): Their cyclic connections make them ideal for sequential data applications, including time series or NLP.Long Short-Term Memory (LSTM) And Gated Recurrent Unit (GRU) Networks: A type of RNN that can learn long-term dependencies. These networks are used in stock market analysis, autonomous automobile track prediction, text-to-speech conversion, and language translation. They require longer training cycles.Generative Adversarial Networks (GANs): They are a type of neural network architecture that consists of two neural networks that work together in an adversarial manner. Commonly employed in unsupervised learning, data synthesis, and image generation. Additionally, transformer networks, deep belief networks, and self-organizing maps are a few specialized decision-making models, each with distinctive strengths. The more suitable neural network design can be selected depending on the task and the type of data being processed. ApplicationsNeural network’s versatility and ability to tackle complex problems have made them a vital tool in artificial intelligence. Neural networks have shown remarkable success in several application areas, such asComputer Vision: Image recognition, object detection, and facial recognitionNatural Language Processing (NLP): Speech recognition, machine translation, and text generationFinancial Forecasting: Stock price prediction and fraud detectionHealthcare: Medical image analysis and disease diagnosisAutonomous Vehicles: Object detection and decision-making systemsRecommendation Systems: Personalized content suggestions on platforms like Netflix and Instagram ChallengesNeural networks serve as vital tools in various industries because of their capacity to identify complex patterns and make reliable predictions. However, they face challenges, including computational complexity, lengthy training periods, and the possibility of overfitting, in which the network learns to remember training data instead of successfully generalizing to new data. Regularization methods and suitable data preprocessing are frequently used to address these problems. To expand the limits of artificial intelligence and decision-making, researchers and practitioners are always experimenting with different neural network topologies to find the best solutions for their particular use cases. Summarizing the Key PointsNeural networks are inspired by the human brain and consist of interconnected layers that process data, making them effective for tasks like pattern recognition and classification.Different types of neural networks, such as CNNs and RNNs, are available for specific applications, including image analysis, natural language processing, and time series forecasting.Despite their strengths, neural networks face challenges like computational complexity and overfitting, hindering their performance and generalization to new data.Ongoing research aims to improve neural network architectures and training methods, enhancing their capabilities in various industry decision-making scenarios. ReferenceTaherdoost, Hamed. “Deep Learning and Neural Networks: Decision-Making Implications.” Symmetry 15, no. 9 (September 8, 2023): 1723. https://doi.org/10.3390/sym15091723.Kufel, Jakub, Katarzyna Bargieł-Łączek, Szymon Kocot, Maciej Koźlik, Wiktoria Bartnikowska, Michał Janik, Łukasz Czogalik, et al. “What Is Machine Learning, Artificial Neural Networks and Deep Learning?—Examples of Practical Applications in Medicine.” Diagnostics 13, no. 15 (August 3, 2023): 2582. https://doi.org/10.3390/diagnostics13152582.“Neural Network In 5 Minutes | What Is A Neural Network? | How Neural Networks Work | Simplilearn.” Video. YouTube, June 19, 2019. https://www.youtube.com/watch?v=bfmFfD2RIcg.

Overview: This article explores Bluetooth technologies, pairing mechanism advancements, and their IoT applications. It highlights security challenges and discusses Bluetooth's secure modes for reliable device communication. The Internet of Things (IoT) proposes a fully networked world in which objects may interact and communicate with each other. Bluetooth and RFID (Radio Frequency Identification) are two of the most popular wireless technologies in IoT applications. What is Bluetooth?The IEEE 802.15.1 standard is the foundation for Bluetooth, a wireless technology. It is utilized for short-range data exchange between stationary and mobile wireless devices and for constructing WPANs (Wireless Personal Area Networks). It was first developed in 1994 as a wireless substitute for RS-232 wires by the telecom provider Ericsson. It uses the FHSS (Frequency Hopping Spread Spectrum) transmission technology and the open, unlicensed 2.4 GHz ISM (Industrial, Scientific, and Medical) radio band to transmit packets while minimizing interference. Over the past 20 years, Bluetooth has advanced from version 1.0 (1999) to version 5.2 (2019), introducing features like improved power efficiency, enhanced security, increased data speed, and extended range. These enhanced features made Bluetooth a significant technology for several IoT applications. What are piconets and scatternets?Bluetooth devices must be linked and verified to one another as part of the pairing authentication process. In the pairing process, the device that starts it is designated as the master, while the other devices that accept the pairing from the master are designated as slaves. A network structure known as a piconet, as shown in Fig. 1, is created when a specific number of slave devices are linked to a single master device. A scatternet, as shown in Fig. 1, is created when at least two piconets are connected.Fig. 1 Illustration of piconets and scatter nets Source: MDPI Bluetooth TechnologiesThere are two primary types of Bluetooth technology:Bluetooth Basic Rate (BR)/Enhanced Data Rate (EDR).Bluetooth Low Energy (BLE) Bluetooth Basic Rate (BR)/Enhanced Data Rate (EDR)Bluetooth Basic Rate/Enhanced Data Rate (BR/EDR), often referred to as Classic Bluetooth. The Bluetooth system functions within the 2.4 GHz ISM band. There are 79 channels in the Bluetooth ISM band, each with a frequency of 1 MHz. The two data transmission modes of classic Bluetooth are as follows:Basic rateEnhanced data rate Basic Rate (BR) employs a shaped, binary Frequency Modulation (FM) to reduce transceiver complexity. BR employs Gaussian Frequency Shift Keying (GFSK) as its modulation, providing a data rate of 1 Mbit/s. Enhanced Data Rate (EDR), which employs Phase Shift Keying (PSK) modulation and has two additional variants: π/4-Differential Quadrature Phase Shift Keying (DQPSK) and Differential Phase Shift Keying (DPSK). It supports data rates of up to 2 Mbit/s and 3 Mbit/s. ApplicationsClassic Bluetooth devices have high-throughput connections.Additionally, any 3G/4G equipped smartphone can serve as a hotspot and give neighboring Bluetooth-connected devices access to the Internet through Bluetooth tethering.Another example of classic Bluetooth products is wireless keyboards that may be connected to a laptop or smartphone.Bluetooth-enabled car stereos that transmit audio wirelessly, allowing hands-free communication.File transfers between any two Bluetooth-enabled devices are another common usage.Bluetooth headsets are a gadget that gains a lot from BR/EDR. It generally consumes more power than Bluetooth Low Energy, making it less suitable for battery-powered devices. It primarily supports point-to-point communication. Bluetooth Low Energy (BLE)Bluetooth Low Energy (BLE), or Bluetooth smart, is an improved version of classic Bluetooth. It also operates in the 2.4 GHz ISM band but uses 40 channels with a bandwidth of 2 MHz each. BLE achieves efficiency by using fewer channels for discovery, which leads to the establishment of rapid connections. The channel spacing of 2 MHz lowers the need for RF filtering. It offers a maximum data rate of 1 Mbit/s, with options for higher rates in newer specifications like Bluetooth 5 BLE, which employs an energy-efficient approach to maintain connectivity while reducing active radio usage. It supports a variety of network topologies, including point-to-point, broadcast, and mesh networks, enabling large-scale device networks. Applications It includes capabilities for device positioning, such as presence detection and direction finding, which are unavailable in BR/EDR. They are suitable for devices requiring infrequent data transmission. Connected sensors in a building (home automation or home care), body-worn health or fitness sensors, heart rate monitors, and various metrology or industrial devices are all examples of BLE applications. Bluetooth Security ChallengesBluetooth devices are susceptible to malicious attacks, includingPIN crackingMAC spoofingMan-In-The-Middle attackBlueJacking attackBlueSnarfing attackBlueBugging attackDenial-of-Service attackFuzzing attackBlueBorne Bluetooth Security: Pairing MechanismBluetooth technology employs various security mechanisms to provide a reliable connection. Pairing enables two Bluetooth devices to undergo a set of security parameters and authenticate each other to derive a master key, known as the link key. This link key is subsequently utilized to generate additional keys that will be employed to ensure secure communications. At present, there are three Bluetooth pairing mechanisms:Legacy pairingSecure Simple PairingSecure Connections Legacy pairingThe original pairing method was used in earlier Bluetooth 1.0 to 2.0 versions. It uses basic algorithms for key generation, simplifying the connection process between devices with limited computational capabilities. Devices exchange a Temporary Key (TK), which is then used to generate a Short Term Key (STK) to encrypt the connection. This process is susceptible to attacks if the TK is weak or predictable. It is vulnerable to various security threats, such as passive eavesdropping and MITM attacks. Secure Simple PairingSecure Simple Pairing (SSP) was implemented in version 2.1 to improve security. The link key is generated using the Elliptic Curve Diffie-Hellman (ECDH) for key exchange. This link key is subsequently utilized to generate additional keys for encryption and authentication. The SSP pairing offers four flexible association modes: Numeric Comparison, Passkey Entry, Just Works, and Out of Band. Secure ConnectionsThey are an enhanced version of the Secure Simple Pairing mechanism, which employs both more robust algorithms and lengthier key sizes. Secure Connections employs AES-CTR for encryption, HMAC-SHA256 for authentication, and P-256-ECDH with HMAC-SHA256 for key generation. In addition, it has implemented the AES-CCM algorithm to provide message integrity services. Security ModesBluetooth devices operate in different security modes, which dictate how security is enforced:Security Mode 1:It is a non-secure mode with no authentication or encryption.Security Mode 2:It provides service-level-enforced security where a centralized security manager controls access.Security Mode 3:It enables link-level-enforced security, which requires authentication and encryption before establishing a physical link.Security Mode 4:Introduced in Bluetooth v2.1 + EDR, this mode uses Secure Simple Pairing (SSP) with Elliptic Curve Diffie-Hellman (ECDH) for key exchange, providing robust security after link setup. Users can better protect their Bluetooth communications from potential threats by understanding and implementing these security features and practices. Summarizing the Key PointsBluetooth technology has evolved significantly, enhancing power efficiency, data speed, and security, making it essential for various IoT applications and device connectivity in modern networks.Understanding Bluetooth's security modes, from non-secure to robust encryption, helps users implement better protection against potential threats and malicious attacks on their devices.Bluetooth Low Energy supports efficient communication with reduced power consumption, making it ideal for applications like health sensors, home automation, and large-scale device networks. Reference“Attacks and Defenses in Short-Range Wireless Technologies for IoT.” IEEE Access 8 (January 1, 2020): 88892–932. https://doi.org/10.1109/access.2020.2993553.Zeadally, Sherali, Farhan Siddiqui, and Zubair Baig. “25 Years of Bluetooth Technology.” Future Internet 11, no. 9 (September 9, 2019): 194. https://doi.org/10.3390/fi11090194.

Overview: The article explores the limitations of silicon-based power devices and highlights gallium nitride as a promising alternative. It discusses the importance of accurate modeling for optimizing circuit designs in power electronics. Power electronics and semiconductor device technologies are vital components for electrical energy conversion to be reliable and efficient. Due to several key advantages, silicon (Si) has been the dominant material for power electronic devices. They are still widely used in power electronics, and their level of development is high. What are the challenges faced by Si-based power devices?Power devices that are primarily Si-based dissipate the largest power losses in a power converter. The challenges faced by Si-based power devices include maximum attainable switching frequency, maximum permissible junction temperature, and maximum reverse voltage blocking capabilities. Si IGBTs, having a high breakdown voltage capability of up to 6.5 kV, are restricted to lower switching rates. Because of their slower switching speeds, large-sized inductive and capacitive elements are employed to manage power. These factors have caused silicon power devices to approach their operational limit regarding performance and efficiency for current power electronic converters. Developing power electronics toward more effective, compact, high-voltage, high-frequency operation requires new developments in power semiconductor devices. Advantages of Gallium NitrideGallium Nitride (GaN), a wide bandgap semiconductor, has gained attention as a possible material for the upcoming generation of power semiconductor devices. GaN has a bandgap of approximately 3.4 eV compared to silicon's 1.2 eV. GaN offers higher carrier density and lower resistance, enabling speeds up to 100 times faster than silicon. GaN has superior thermal conductivity, allowing for better heat dissipation in high-power applications. Importance of Modeling of GaN DevicesA prototype that can simulate the intended performance characteristics of the circuit must be used to develop power electronics circuits. This enables more efficient development of high-performance power electronics systems. Accurate models allow engineers to predict and optimize the performance of GaN devices without extensive physical prototyping. Models help verify designs before fabrication, reducing development time and costs associated with physical prototyping and testing. The semiconductor device model is a crucial component of circuit simulations to predict design performance, offers a structure for design centering and tolerancing, and facilitates troubleshooting. There is a need for a precise compact model of the GaN power devices in the market. Fig. 1 depicts the evolution of various GaN HEMT models. Fig. 1 Evolution of GaN HEMT large-signal models. Source: ScienceDirect Classification of GaN ModelingThe modeling of GaN semiconductor devices can be classified into several main categoriesEmpirical ModelsPhysics-Based ModelsCompact ModelsBehavioral ModelsLarge-Signal ModelsThermal ModelsTrapping ModelsMulti-Physics ModelsThis article provides an overview of both empirical and physics-based models. Empirical ModelsEmpirical models were the typical models to emerge first, mostly because they characterize HEMT performances using relatively simple expressions. Examples includeAngelov modelDynaFET modelEEHEMT modelStatz and Crutice models These models are based on hyperbolic tangent functions. The accuracy, user-friendliness, and high degree of adjustable nature of the empirical models make them extremely suitable for a wide range of industrial applications. Angelov ModelIn recent years, a number of GaN-based device models have become available. For RF HEMT devices, as well as other Si and SiC devices, one of the common models is the Angelov model, which has been employed extensively. Numerous updated Angelov models have emerged in recent years to address the evolving requirements of various new application scenarios. The Angelov model is a widely used large-signal model for modeling GaN HEMTs and other field-effect transistors. Uses exponential and hyperbolic tangent functions to model I-V characteristics. Designed to accurately capture the nonlinear behavior of FETs, especially for RF/microwave applications. However, because the model is entirely empirical and has been in widespread use for a long time, it may be applied to any semiconductor device. DynaFET ModelArtificial neural network (ANN)--based GaN HEMT models are commonly employed in machine learning (ML)-based GaN HEMT models. Naturally, the ANN-based models can effectively describe a device's nonlinearity with a low computing cost because of their great fitting ability and reasonable deployment cost. A common example of an ANN-based model is Keysight's DynaFET model. Physics-Based ModelsEfforts were directed toward developing GaN HEMT models based on the underlying physical characteristics. These models are grounded in the fundamental physics of the device. These models show a far higher scalability than empirical models. Physics-based models includeMIT Virtual Source (MVS) HEMT modelAdvanced SPICE Model (ASM) HEMT modelHiroshima-University Starc Igfet Model for GaN HEMT (HiSIM GaN HEMT model)École Polytechnique Fédérale de Lausanne (EPFL) HEMT model Rigid physical equations serve as the foundation for physical models. Physical models are more scalable, compact, and robust than empirical models. MIT GaN ModelMIT GaN model, also known as the MIT Virtual Source GaNFET-High Voltage (MVSG-HV) model, is a physics-based compact model developed for GaN HEMTs. This model has been validated for an EPC GaN device and for depletion-mode RF devices. Additionally, the model is able to simulate charge trapping and radiofrequency noise under high-frequency RF power amplifier operation. However, the model has proven to be reliable and capable of good convergence on depletion-mode RF GaN devices. ASM-HEMT ModelThe ASM-HEMT (Advanced SPICE Model for High Electron Mobility Transistors) is a compact model developed specifically for GaN HEMTs. It is a physics-based compact model for GaN HEMTs designed for accurate circuit simulation of GaN devices. It has a surface potential-based approach for improved scalability and physical accuracy. It is based on using Schrodinger's and Poisson's equations to formulate the surface potential in the channel. This model has been proven to have both small- and large-signal characteristics appropriate for RF devices. It is also applicable to power electronics, and it is highly suitable for RF GaN applications. In conclusion, the GaN HEMT large-signal models face numerous obstacles in the 2020s and beyond. Advances in semiconductor technologies are the source of some of them. The lack of physical meaning in empirical models results in poor scalability. Also, physical models may be less widely applicable due to their complexity and lack of tunability. Artificial intelligence and measurement technology are changing quickly, so it will be interesting to see if they can lead to new models. Summarizing the Key PointsGallium nitride offers significant advantages over silicon, including higher efficiency, faster switching speeds, and superior thermal conductivity, making it ideal for modern power electronics applications.Accurate modeling of GaN HEMTs is crucial for optimizing circuit designs, reducing development costs, and enhancing performance, enabling engineers to predict device behavior without extensive prototyping.Various modeling approaches exist, including empirical and physics-based models, each with unique benefits,understanding these can help select the proper model for specific applications. ReferenceKotecha, Ramchandra M., Md Maksudul Hossain, Arman Ur Rashid, Asif Imran Emon, Yuzhi Zhang, and H. Alan Mantooth. “Compact Modeling of High-Voltage Gallium Nitride Power Semiconductor Devices for Advanced Power Electronics Design.” IEEE Open Journal of Power Electronics 2 (January 1, 2021): 75–87. https://doi.org/10.1109/ojpel.2021.3055531.Luo, Haorui, Wenrui Hu, and Yongxin Guo. “On Large-Signal Modeling of GaN HEMTs: Past, Development and Future.” Chip 2, no. 3 (September 1, 2023): 100052. https://doi.org/10.1016/j.chip.2023.100052.

Overview: The article reviews switching diodes, explaining their fundamental operation, key characteristics, and advantages in electronic circuits. It highlights their rapid switching capabilities and applications in high-frequency environments. The most essential function in a circuit is switching. Semiconductor devices that are specifically designed for rapid switching applications are switching diodes. In forward voltage, they allow current to flow; in reverse voltage, they block the current. This functionality makes them a basic component in every electronic circuit. What is a switching diode?Switching diodes, as shown in Fig. 1, are semiconductor devices that have the ability to switch on and off rapidly. They are increasingly employed in high-frequency applications because of their transition ability to switch from a conductive state to a non-conductive state. A diode suitable for switching small signals of up to 100 mA is a switching diode. They are designed to handle and withstand low voltages ranging from 80 V to 200 V. This property reduces the junction area of switching diodes. Hence, low capacitance and a short reverse recovery time can be realized. Switching diodes are modeled to control the flow of current in a circuit. Working PrincipleThe fundamental operation of a switching diode is based on its ability to conduct current in one direction (forward bias) and block it in the opposite direction (reverse bias), as shown in Fig. 2. When a voltage is applied in the forward direction, the diode turns on, allowing current to flow. Conversely, when a reverse voltage is applied, the diode turns OFF, preventing current flow.          Fig. 2: Working of switching diodes in (a) forward bias and (b) reverse bias. Source: ROHM Semiconductor The switching time required to change from on to off or off to on is shorter than that of normal diodes. The one-way conductive characteristic of switching diodes has a very low resistance of hundreds of ohms in positive bias. In contrast, there is a high resistance of hundreds of kilo-ohms in negative bias. This on/off behavior is akin to a switch in a circuit. Key Characteristics of a Switching DiodeThe essential characteristics of an ideal switching diode areHigh switching speedLow forward resistanceHigh reverse resistanceLow barrier capacitanceLong durabilityCompact sizeHigh reliability Reverse Recovery TimeOne of the critical parameters for switching diodes is the reverse recovery time. It is the time taken by the diode to switch from the ON state (low resistance state) to the OFF state (high resistance state), whereas switching from the OFF to the ON state is turn-on time. A shorter reverse recovery time is desirable, leading to lower energy losses and switching speeds. Typical switching diodes have a reverse recovery time ranging from a few nanoseconds to several hundred nanoseconds, depending on the type (e.g., high-speed or ultra-high-speed diodes) and the materials used in their construction. Barrier CapacitanceA barrier capacitance is connected in parallel with the diode. Under high-frequency and extreme conditions, current directly passes through the barrier capacitor, bypassing the diode. To avoid this situation, the barrier capacitance of the switching diode is kept extremely low. Low barrier capacitance will provide good unidirectional conductivity. Factors Affecting the Working of a Switching DiodeThe other factors that influence the working of switching diodes areCapacitance: Junction capacitance impacts the switching time.Resistance: The diode changes its state according to the resistance offered.Doping concentration: The density of charge carriers affects the switching speed.Depletion region: Narrow depletion width allows faster switching. Types of Switching DiodesSwitching diodes can be categorized based on their performance parameters:Ordinary Switching Diodes: General-purpose diodes used for basic switching applications.High-Speed Switching Diodes: Designed for faster switching times and suitable for high-frequency applications.Ultra-High-Speed Switching Diodes: The fastest switching capabilities are ideal for advanced electronic applications.Low-Power Switching Diodes: Consume less power but have higher reverse recovery times than high-speed diodes.High-Back Pressure Switching Diodes: They can withstand higher reverse voltages, making them suitable for specific applications. AdvantagesSwitching diodes offer several advantages over conventional diodes.Fast Switching: They can switch states in nanoseconds, making them suitable for high-frequency applications.Energy Efficiency: They consume less power than mechanical switches, which is particularly beneficial for battery-operated devices.Compact Size: Their small form factor allows for integration into compact electronic circuits.Reliability: Switching diodes are less prone to wear and oxidation than mechanical switches, leading to longer operational lifespans. ApplicationsSwitching diodes are widely used in various electronic circuits, including:Pulse and Switching Circuits: To control current flow in electronic devices and digital circuits.High-Frequency Circuits and Applications: Their low capacitance allows for efficient operation in RF applications where rapid switching is essential.Rectification: They are employed in switched-mode power supplies to convert AC to DC.Voltage Clamping: Used to protect circuits from voltage spikes.Signal Detection: In circuits that require fast response times for signal processing.Transistor protection: To ensure the safety and reliability of electronic circuits by protecting transistors from reverse voltage and unnecessary dischargeDigital logic: Diode logic circuits are utilized to implement basic logic functions. A Switching Diode to ConsiderThe 1N4148 is a widely used silicon switching signal diode known for its reliability and cost-effectiveness. It is commonly used in switching applications up to about 100 MHz, with a reverse recovery time of no more than 4 nanoseconds. The diode, which is shown in Fig. 3, was registered at JEDEC in 1968 for military and industrial applications and is available from various manufacturers. Fig. 3: Silicon Switching Diode. Source: Kynix Semiconductor Specifications for the most commonly used switching diodes (1N4148) areForward voltage ranges from 0.4 to 1.4 VThe reverse voltage is 100 VThe diode capacitance is 4 pFThe average forward current is 200 mAPower dissipation is 500 mWThe maximum reverse recovery time is 4 ns In summary, switching diodes are crucial and essential components in modern electronic circuits, providing reliable and efficient switching capabilities essential for various applications. Their design and performance characteristics, particularly the reverse recovery time, significantly affect their performance in high-speed and high-frequency environments. Summarizing the Key PointsSwitching diodes are essential semiconductor devices that enable rapid switching in electronic circuits, allowing current to flow in one direction while blocking it in the opposite direction.Key characteristics of switching diodes include high switching speed, low forward resistance, and low barrier capacitance, making them ideal for high-frequency applications.The reverse recovery time is a critical parameter for switching diodes, as shorter times lead to lower energy losses and improved switching speeds in electronic circuits.Switching diodes can be categorized into ordinary, high-speed, ultra-high-speed, and low-power types, each designed for specific application performance needs. ReferenceTan Yi Liang, Nor Farhani Zakaria and Shahrir Rizal Kasjoo, “ Silicon Self-Switching Diode (SSD) as a Full-Wave Bridge Rectifier in 5G Networks Frequencies,” MDPI Sensors, Volume 22, Issue no. 24, Dec 2022. https://www.mdpi.com/1424-8220/22/24/9712 “Switching Diode: Working and its applications” https://www.elprocus.com/switching-diode/

Overview: The article discusses the role of fuses as crucial electrical safety devices that protect circuits from overcurrent. It highlights their construction, types, advantages, limitations, and applications. In recent years, DC microgrids have become modern distribution systems that have become more commonly deployed compared to AC microgrids because of the great advantages they offer, including improved efficiency, reliability, and easier conversion steps. The increased usage of DC microgrids is very much needed for future power systems to be load-adaptive. However, the installation of DC microgrids faces challenges regarding the protection of the devices. Power electronic devices that can withstand two to three times the standard current for a brief period of time can protect DC microgrids during fault current. Hence, to handle fault currents and prevent the risk of sources and loads, a proper selection of protection devices with basic requirements is needed. What are circuit breakers?These protection devices should have relatively higher efficiency, fast response, simplicity of construction, minimal power loss, reliability, and affordability. Circuit breakers are essential components in electrical systems, serving critical functions to ensure safety, reliability, and efficiency. Their main objective is to safeguard electrical circuits from harm due to overcurrent, short circuits, or other electrical faults. The most commonly employed protection devices includeFusesMechanical circuit breakersSolid-state circuit breakersHybrid circuit breakers They are an electrical safety device that interrupts the flow of current when a fault is detected. Protects electrical systems from damage due to overload or short circuits. Under normal conditions, the circuit breaker allows current to flow. When a fault occurs, it automatically "trips" or opens the circuit, stopping the flow of electricity. What is a fuse?A fuse is an electrical safety device made up of a thin piece of wire designed to handle a certain threshold of current, as shown in Fig. 1. It is in the form of a metallic conductor made up of zinc, copper, silver, aluminum, or other alloys, which melts up when the current reaches a certain threshold. The fuse wire is connected to two metal terminals, which connect it to the circuit. For arc extinction, the fuse wire is encased in a non-combustible box or cartridge filled with material like quartz sand, which provides insulation and protection when the fuse blows up.Fig. 1 A picture of an electrical fuse. Source: Kynix Working PrincipleFuses are more commonly employed as circuit breakers that are connected in series to the electronic component to be protected from fault currents. The resistive heating of the current is the principle involved in the fuse's working. When the current flows through a conductor with a certain resistance, the power loss is dissipated as heat. Under normal conditions, heat is dissipated from the fuse wire to the surrounding environment. In the case of fault current, when excess current passes through the fuse wire beyond a certain limit, the fuse wire excessively heats up and melts, as shown in Fig. 2. This breaks up the circuit and prevents damage to the expensive electronic component connected to it in series.Fig. 2: Diagrammatic illustration of the workings of the fuse. Source: Rakesh Kumar, Ph.D. TypesFuses are broadly classified asFast-acting fusesTime-delay fusesFast-Acting FuseAs the name implies, these fuses have a faster response time and are used to protect sensitive electronic equipment, most commonly the output of converters and batteries.Time-Delay FuseThey are used in high-frequency current peaks that occur during starting motor or energizing loads, which are normal temporary current surges in the circuit. AdvantagesFuses are reliable protection devices that are comparatively the most affordable protection devices against overcurrent when compared to other protection devices. They are simple to construct and readily available, require no maintenance, and are replaced after being exposed to overcurrent. DisadvantagesFuses act as weak points in the circuit that burn up and have to be manually replaced after each episode of fault current. This single use is one of the significant drawbacks; additionally, it cannot differentiate between transient and permanent faults. Fuses are used as the backup protection device for the main switch in the case of power converters. They are not the preferred option for applications requiring fast response times, and more advanced protection devices like solid-state circuit breakers are alternatively used. Selection of a FuseSpeed is an important parameter in the proper selection of the fuse. For AC circuits, the response time should be between 10-100 ms, and for DC circuits, for the fuse to operate optimally, the response time should be as fast as 0.5 ms. Semiconductor devices require ultra-fast response fuse since they can get heated up quickly. The current rating of the fuse should be greater than the circuit's operating current. Additionally, the breaking capacity of the fuse should be greater than the short circuit current. ApplicationsFuses play a critical role in safeguarding sensitive electronic components from fault currents. Fuses are more commonly employed in batteries and photovoltaic cells as economical circuit protection devices. They are also used in load feeders that function with switches and relays. They are more commonly preferred alternative options for mechanical DC breakers. Fuses are an effective means of protection and are more commonly used to protect household circuits, electrical vehicle systems, industrial machinery, and equipment from fault currents. Littelfuse FusesLittelfuse manufacturers offer the widest collection of fuses that serve all applications for modern electronic systems.Types of Littelfuse FusesThere are various types of fuses designed to serve specific applications. A few of the main types are explained below: Industrial Fuses:Class L, J, T, H, G, RK5, RK1, K5, Class CC Fuses, Midget Fuses, and semiconductor fuses are the most common industrial fuses available today and enable an innovative selection of fuses for various applications. Cartridge FusesCartridge fuses are used in various applications, including commercial, industrial, automotive, residential, and agricultural applications, and they are available in a variety of sizes, amps, and volt ratings. Surface Mount FusesMore commonly available surface mount type fuses are FLAT PAK fuses, Nano 2 fuses, PICO fuses, and thin film chip fuses, which are commonly used in overcurrent protection applications. Axial Radial Thru Hole FusesA wide variety of axial radial thru-hole fuses are available to meet specific customer demands, including our PICO fuses, HVAC fuses, and Micro TR3fuses, hazardous area-type fuses, and more. There are various other types, including specialty power fuses, medium voltage fuses, military high-reliability fuses, and AEC-Q200-qualified fuses. To conclude, fuses are a more dependable option for safeguarding electrical devices from faulty currents, and the proper selection of fuses for proper current rating application is an important criterion. Summarizing the Key PointsFuses are critical safety devices that protect electrical circuits from overcurrent by melting and interrupting the current flow, preventing damage to connected components during faults.There are two main types of fuses: fast-acting fuses for sensitive electronics and time-delay fuses for handling temporary current surges during motor starts or load energization.Fuses are reliable and affordable protection devices that require no maintenance, but they must be manually replaced after use, which can be a drawback in applications that need quick resets.Proper selection of fuses is essential, considering factors like response time, current ratings, and breaking capacity, to ensure optimal performance in various electrical applications.Fuses are widely used in household circuits, industrial machinery, and renewable energy systems, such as batteries and photovoltaic cells, highlighting their versatility in circuit protection. ReferenceBayron Perea-Mena et al., “Circuit Breakers in Low- and Medium-Voltage DC Microgrids for Protection against Short-Circuit Electrical Faults: Evolution and Future Challenges,” Applied Sciences 12, no. 1 (December 21, 2021): 15, https://doi.org/10.3390/app12010015.Infinity Learn NEET, “What is an Electric Fuse? | Don’t Memorise,” September 7, 2018, https://www.youtube.com/watch?v=BLIYsRwKrkE.“Fuses - Types of Fuses - Littelfuse,” n.d., https://www.littelfuse.com/products/fuses.aspx.