The Kynix Blog

Overview: This article provides an in-depth analysis of the challenges in state of charge estimation for lithium-ion batteries in electric vehicle applications. Additionally, the article explores the impact of thermal stability on battery performance. An important parameter of a battery management system is the state of charge (state of charge), which indicates the remaining battery charge. Furthermore, for effective electric vehicle operation, a precise and reliable state of charge estimation is greatly important. The two main approaches to assessing the state of charge that have been around for a while are data-driven and model-based. The background process information is used to construct model-based state of charge estimate methodologies, which are also called white-box models. The conventional method, which is based on models, is capable of solving many problems, particularly in the engineering arena. Conversely, the emergence of large amounts of data and powerful computers has made relatively new ways to estimate the state of charge that are data-driven possible. Data-driven approaches, sometimes called black-box models, rely on real-world observations without understanding the underlying mechanisms. CatalogHow difficult is it to estimate a battery's state of charge?Lack of AccuracyEffects of Charging MethodsThermal StabiltyRole of Battery capacitySummarizing the Key PointsReference How difficult is it to estimate a battery's state of charge?However, there are a lot of variables that affect state of charge estimation, including battery age, ambient temperature, and many other factors, making it a complicated procedure. Improving algorithm robustness, accuracy, and computational complexity at a low cost is the main target for state-of-charge estimation of lithium ion batteries. It will enable the method to be implemented in low-cost battery management system hardware. The goal is to identify an effective state of charge algorithm that can balance compactional complexity and accuracy. Typically, a variety of sources contribute to state of charge error generation, such as current and voltage sensors, erroneous battery models, the initial state of charge, and incorrect parameter choices made during optimization. Consequently, the development of a technology with low causes of state of charge errors is required. This Part 1 article discusses some of the main problems and difficulties. Lack of AccuracyHundreds of cells coupled in series or parallel make up the lithium-ion battery pack in an electric vehicle, which satisfies the need for high voltage and energy. The state of charge estimation of the lithium-ion battery pack is still hard to track and difficult to monitor. Because of the physical changes brought about by repeated cycles of charging and discharging, each battery cell in a lithium-ion battery pack exhibits an inconsistent state of charge. The state of charge divergence demonstrates that manufacturing techniques and tolerances, material flaws that arise under various working conditions, and aging battery cells are all factors in different battery cell performance. The state of charge imbalance within the lithium-ion battery pack, which rarely provides reliable information, affects power, energy computation, and lithium-ion battery safety systems. To solve the state-of-charge balancing issue, a number of techniques have been developed recently, such as cellCalculation-based methodsScreening process-based approachesBias correction methods Effects of Charging MethodsIn recent years, the lithium-ion battery charging strategy has drawn a lot of attention for electric vehicle applications. Developing fast electric vehicle charging technology is challenging. The lithium-ion battery's lengthy charging process may make people less interested in electric vehicle adoption as a whole. Conversely, rapid charging techniques that rely on charging current acceleration produce heat, which has a negative impact on battery longevity. Therefore, it is a difficult task to design an efficient charging strategy that maintains a fair balance between heat, lifespan deterioration, and charging efficiency. The battery's state of charge assessment is significantly impacted by the charging procedure. Estimating the state of charge mostly depends on the battery's condition, which is highly dependent on the charging procedure. Thermal StabiltyIn order to increase electric vehicle performance and acquire the correct state of charge, more research is necessary to address the major problem of state of charge estimation under high temperatures. The most typical causes of thermal runaway are heat, mechanical, or electrical misuse. Mechanical abuse in the form of penetration or collision is what causes a short circuit. Exothermic reactions, lithium plating, and overcharging are the main causes of electrical abuse. Ineffective thermal management and high temperatures are the root causes of heat abuse. An increased number of charge/discharge cycles causes thermal runaway. There is a layer called the solid electrolyte interface (SEI) that forms on top of the anode materials in lithium-ion batteries when the electrolyte breaks down. Table 1 shows the impact of thermal runaway on various types of lithium-ion batteries. When the temperature rises above 90°C, the solid electrolyte interface layer, negative electrode, and electrolyte begin to decompose. Table 1: Effect of thermal runaway on various types of lithium-ion batteries. Source: IEEE AccessTemperatureEffects90-120°C● Solid electrolyte interface starts decomposing● Heat releases● Temperature risesAbove 120°C●  Electrolyte and lithium react● Solid electrolyte interface cannot cut off the contact between the anode and the electrolyte.Above 150°C● LiCoO2 breakdown, releases oxygen● Separator begins to melt and blockAbove 160°C    LiNi0.5Co0.15Al0.05O2 breakdown, release oxygenAbove 200°C● Electrolyte decomposition● Flammable gases● Safety valve opensAbove 210°C    LiCoxNiyMn2O2 breakdown, releases oxygenAbove 265°C    LiMn2O4 oxidated, releases oxygen300°C● Temperature rises sharply● Fire● Thermal runawayAbove 310°C●  LiFePO4 breakdown, releases oxygen However, as seen in Table 1, because of its restricted exothermic heat discharge, LiFePO4 exhibits superior thermal stability compared to other lithium-ion battery materials. Role of Battery capacityThe battery's active material begins changing at the rate of discharge, causing capacity loss. When the internal impedance of the battery goes up, on the other hand, the working voltage and power rate capability go down. With capacity and power fading, state of charge error rates rise. As demonstrated in Fig. 1, there is a link between temperature and capacity fade, where the maximum charge storage capacity begins to decrease when the temperature increases by 45°C. Fig. 1 The relationship between battery charge storage capacity and temperature. Source IEEE AccessFurthermore, it has been shown that capacity decreases as the aging cycle progresses. Similar results also appear where it is observed that when temperature increases from 37°C to 55°C, capacity fades from 40% to 70%. As advised by the manufacturer, capacity loss is also observed in batteries when the voltage is raised above the threshold value. Summarizing the Key Points●State of charge estimation and thermal stability are critical factors in the performance and safety of lithium-ion batteries in electric vehicles.●Challenges in state of charge estimation include factors such as battery age, ambient temperature, and manufacturing variations.●Advancements in data-driven and model-based approaches offer potential solutions for accurate state of charge estimation.●Thermal stability issues, such as thermal runaway and capacity fading, significantly impact battery performance and safety.●Techniques for state-of-charge balancing and efficient charging strategies are essential for enhancing electric vehicle battery performance.●Continued research and development are necessary to improve the accuracy and reliability of state of charge estimation and thermal management for lithium-ion batteries in electric vehicles. ReferenceHow, Dickson N. T., M. A. Hannan, M. S. Hossain Lipu, and Pin Jern Ker. “State of Charge Estimation for Lithium-Ion Batteries Using Model-Based and Data-Driven Methods: A Review.” IEEE Access 7 (2019): 136116–36. https://doi.org/10.1109/access.2019.2942213.

Kynix, a well-known electronic component distributor, recently announced its participation in NEPCON JAPAN 2024. The exhibition will take place from Wednesday, January 24th to Friday, January 26th, 2024, at Tokyo Big Sight in Japan. As a popular electronic component distributor, Kynix will be showcasing in the ELECTRONIC COMPONENTS & MATERIALS EXPO section of the exhibition. NEPCON JAPAN is the leading exhibition for electronics manufacturing and R&D technology in Asia. It consists of seven specialized exhibitions covering important areas in electronics manufacturing and R&D, providing a one-stop platform for all professionals in the electronics industry in Asia. The exhibition has been held for over 30 years and has evolved with the development of the Japanese and Asian electronics industry. It covers the fundamental areas of the electronics industry, including manufacturing, R&D, and packaging technologies. NEPCON JAPAN 2024 (Tokyo) is reported to have 1,900 exhibitors and 85,000 visitors, with participating countries/regions including China, the United States, Australia, France, Hong Kong, and more. The exhibition is of significant scale, with heavyweight participating companies and considerable influence. Kynix feels honored to be one of the attending brands. Kynix is a renowned electronic component distributor headquartered in China, with stable partnerships with leading electronic component manufacturers and suppliers worldwide, ensuring a product line that covers a wide range of market demands. Kynix offers various types of electronic components, including integrated circuits, sensors, capacitors, resistors, inductors, memory modules, switches, connectors, displays, and more. Kynix is committed to providing high-quality electronic components, ensuring product reliability and stability through strict quality control and supply chain management. Currently, Kynix has established a good reputation and customer base in the industry, thanks to its hardware strength in warehousing logistics, operational services, and supply chain management. Through NEPCON JAPAN 2024 (Tokyo), you can not only learn about Kynix's competitive advantages but also witness its latest developments in the field of electronic components. Kynix will use this exhibition as a platform to communicate with customers, showcasing its corporate strength and brand presence comprehensively. With the upcoming NEPCON JAPAN, Kynix sincerely invites both new and existing customers to visit its booth, where our team can discuss business needs and collaboration opportunities. We look forward to meeting you at the NEPCON JAPAN exhibition! 

Overview: If you are looking to choose between the contemporary DDR5 and the classic DDR4 but are overwhelmed with the technical intricacies of both, then don’t worry anymore. Whether you are a tech enthusiast or someone simply curious about the DDR4 vs DDR5 debate, this article will unravel a lot for you. Let's hope this is your last read before you finally put an end to the DDR4 vs DDR5 debate.   The memory of a computer is a powerhouse that dictates the efficiency of the system and data processing. Of the two main types of computer memory, Random Access Memory (RAM) is a critical component of a computer’s architecture. It provides fast and temporary storage for actively used data. The capacity and speed of RAM notably influence a system’s performance, especially in computers where multiple applications are being used at a time.   For the past ten years, DDR4 RAM has been the only available on most PCs. It has a 128 GB memory and speeds up to 5000 MHz. However, the year 2021 marked a revolution for RAM, and the introduction of DDR5 not only revolutionized computing but also initiated a constructive dialogue around the comparison of the two. Technical Comparison Technical comparison of DDR4 and DDR5 gives interesting insights into the speed, bandwidth, latency and power efficiency of the two. Clock speed (the number of times the RAM modules can access its memory per second) is one of the first parameters that comes to mind when comparing DDR4 and DDR5. The clock speed for DDR4 is 2133 MHz (the default rate), while it is 4800 MHz for DDR5. It is a considerable difference and makes DDR5 a clear winner in speed. Speaking of the bandwidth or the data transfer rate, DDR4 will run at a speed of up to 3200 MT/s (for Intel 12th Generation Processors). On the same processor, DDR5 runs up to 4800 MT/s. This comparison gives us the exact stats on the data transfer rate, which comes out to be 25.6 GB/s for DDR4 and 38.4 GB/s for DDR5, giving DDR5 a clear win over the competitor. However, the comparison of latency seems to break the winning streak of DDR5. The CAS (Column Address Signal) latency is 20 for a DDR4-3200 CL20 module, while most of the DDR5 modules have CL40 CAS latency. As a result, DDR-3200 CL20 RAM has a quick operation as compared to the DDR-4800 CL40 module. However, the future of the latency of DDR5 seems brighter as the G.Skill Trident Z5 sticks have a CAS latency of 28. Factoring in its speed yields a latency of 10 nanoseconds, which is competent with DDR4. In conclusion of the technical comparison, it would be right to state that DDR5 is the definitive winner. Compatibility Analysis Speaking of the most recent stats, DDR5 has limited compatibility. Intel’s 12th-gen “Alder Lake” and 13th-gen “Raptor Lake” processors and AMD’s 6000-series mobile and 7000-series desktop processors support DDR5 modules. Almost all of the processors manufactured in the last ten years support DDR4 RAM. It includes Intel’s 12th-generation processors as well. However, the 13th-generation desktop processors by Intel are compatible with both DDR4 and DDR5.   Performance Evaluation Before comparing the most critical aspect, i.e., the performance, DDR5 seems to be doing quite well so far. However, it does come down to performance evaluation because specs are of little to no use without efficient performance. DDR5 RAM gives a swift performance as compared to DDR4 RAM while rendering a 3D graphics scene using Blender. The time difference is calculated to be almost two minutes between the two competing RAMs. Similarly, DDR5 is about one minute quicker than DDR4 when encoding a video file using Handbrake. Other tasks, such as the gaming ones show no considerable performance difference between DDR4 and DDR5. A worth-noting here is that with Nvidia-based graphics benchmark, DDR4 performed well by a 20-fps margin for some games. In short, it is difficult to rule out one RAM while evaluating performance.   Price and Availability When DDR5 was introduced in 2021, it was high-priced. In 2021, 16 GB of DDR5 RAM was worth $1000. Now, it is cut down to $3 per GB, which means you can get the same 16 GB for less than $50 now. For greater speed and improved timings, the price increases. For instance, a 32 GB dual-channel DDR5 RAM at 5600MHz will cost up to $120, while a 16 GB kit in the 5600 MHz range will cost up to $50.   Speaking of availability, DDR5 comes with Intel’s Alder Lake 12th generation (standard), Raptor Lake 13th generation (standard), and AMD’s Ryzen 7000 Zen 4 CPU (exclusive). However, if you are opting for a custom PC, you can acquire DDR5 RAM from various retailers, such as Best Buy, Newegg or your preferred electronic store.   Upgrade Recommendations Finally, it comes down to whether one should upgrade to DDR5 or stick with DDR4. As a gamer, upgrading to DDR5 is the right decision for improving the experience. A high-rated bandwidth and a high-frequency option, such as DDR5, in your gaming PC can improve frame rates as well. However, there won't be any other significant differences from DDR4 for gamers.   DDR5 upgrade is more fruitful for professional designers due to higher data transfer rates. Overall, improved system responsiveness and quick data processing make DDR5 a good pick for video editing and other graphic design jobs.   Future Trends In the future, DDR5 will become a necessary upgrade due to compatibility and support issues and will completely replace DDR4. Considering the key factors such as the bandwidth, performance gains and the price gap seem to favor DDR5. The availability of DDR5 with Intel’s 12th and 13th-generation processors gives off a dynamic power display, unlike the ones seen before. Plus, the pairing of DDR5 with the new AMD Ryzen 7000-series processors will give rise to new horizons of power and efficiency. One point is clear: DDR5 might take a couple of years to replace DDR4, but it is here to stay for longer.

Overview: The article discusses the importance of maintenance in ensuring the reliability and safety of power electronic systems. It outlines the steps involved in maintenance, including condition observation, anomaly identification, defect diagnosis, and remaining useful life prediction. Power electronic systems are subject to a variety of risks, including catastrophic failures, despite the careful consideration of dependability characteristics during design and control. This is because of the complex and demanding operating settings of power electronic systems. For field applications, power electronic components, converters, and systems must be extremely reliable and safe. What are the steps in maintenance to make the power electronic system more reliable?Preventive maintenance systems are useful ways to guarantee that planned functions are carried out as intended. The steps in maintenance of power electronic system includesCondition observationIdentification of anomaliesDiagnosing defectsRemaining Use Life (RUL) predictionThe above actions coincide with the IEEE standard framework of prognostics and health management for electronic systems. Condition ObservationPower electronics condition observation consists ofIdentification of system parametersPreprocessing dataMining featuresThe data from the condition observation is used to discover informative and hidden patterns that form the foundation for the prognostic and health management applications that follow. Identification of System ParametersIdentification of system parameters involves the gathering of data for important components.Characteristics of power electronic systems includesExtremely small space inside a power moduleExtremely fast switching frequencyRelatively insignificant parameter changes in terms of aging, etc.Because of these characteristics, developing specific hardware for parameter identification is quite a challenging task.A noninvasive approach that uses existing physical signals to indirectly get information or estimate relevant information without the need for additional hardware implementation is one of the more promising methods.Therefore, a sensorless and cost-effective option can be used for condition monitoring, which is good for people who work in industry. In general, there are two types of methods for identifying system parameters:Model-freeModel-based. Preprocessing data and Mining featuresThe goal of data preprocessing and feature mining is to improve the quality of the raw data so that it can be used for applications like problem diagnostics.Improving the quality of data involves the following steps to make it more organized. The steps are as followsData cleaning to minimize noiseData clustering is used to find groups of related data pointsDensity estimation is used to determine the distribution of the dataData compression to reduce the number of features by projecting large-sized data to small-sized dataData fusion to combine various information sources, and moreWhen data preparation and feature mining are done correctly, the performance of the ensuing prognostics and health management applications—such as diagnostic accuracy—can usually be greatly enhanced. Identification of Anomalies and Diagnosing DefectsThe anomaly detection process focuses on identifying unusual patterns and making a binary decision. When the nominal parameters or rated system characteristics exceed the predetermined safety range, it gives an indication.The fault diagnosis finds and identifies the specific failure modes after the unusual changes happen.The classification, regression, or clustering tasks are essentially anomaly detection and fault diagnosis. When a new fault signature arrives, it identifies the fault label based on the learned relationship from the training stage.Anomaly detection and fault diagnosis techniques fall into two categories:Supervised learningUnsupervised learning Remaining Useful Life (RUL) PredictionIn the design phase, lifetime prediction serves to support the characteristics of a population of units known as the ‘Design for Reliability’. It is one of the crucial components of prognostics and health management.The purpose of the estimation of RUL is not to accurately predict the lifespan of a population of units. Based on condition monitoring data, it predicts the remaining lifespan of each single unit in operation. For applications where availability, safety, or reliability are crucial, RUL prediction is used as an extra tool to lower uncertainty.The lifetime estimate is subject to several challenges, such asInaccuracies in model calibrationManufacturing tolerancesDifferences in operational environments and workloadWhen a particular unit is operated in the field, these uncertainties lead to inaccurate reliability estimations. The following areas require greater attention in order to improve the practicality of AI-based RUL prediction techniques for field applications. Quantification of uncertaintyFor RUL prediction, being able to measure uncertainty is more important than for other regression-related tasks, like control functions. Since the RUL is a random variable, quantifying the confidence interval is crucial for making the best decisions.All of these uncertainties—due to population heterogeneity, measurement noise, various operating settings, etc.—should be considered in a workable practical solution. Quantifying the uncertainty using AI algorithms is quite difficult.A few practical options areThe use of particle filters in neural networks (NNs)Bayesian-based artificial intelligence techniques (e.g., Gaussian process, RVM)Monte Carlo methodsStochastic data-drivenStochastic, data-driven approaches are an interesting option to explore. These approaches can naturally yield the probability density function of the RUL for the purpose of computing the confidence interval. Adaptive capabilityThis is the crucial stage for real-world applications and is related to the model parameter tuning layer in Fig. 1 that connects the offline and online models. If an AI approach lacks adaptive flexibility, its use is limited.Power electronics have difficulties because the operational conditions of the training dataset, which is often acquired through accelerated testing trials, differ significantly from those of the in-situ system (i.e., the test data). Most of the research makes the assumption that the in-situ system's operational parameters are the same as those of the training dataset, which could not be the case in real-world applications.Therefore, the AI-based RUL prediction method's adaptability is essential for bridging the gap between research in academia and practical implementations in industry.Detailed mapping relationship derivations and transfer learning of degradation characteristics under different operating settings (temperature, voltage, humidity, etc.) are also interesting ways to tune model parameters. This means that system models need to be studied in great detail.Fig. 1 shows a methodical flowchart of power electronic system maintenance tasks. It typically comprises the three elements listed below.             Summarizing the Key PointsMaintenance of power electronic systems involves condition observation, anomaly identification, defect diagnosis, and remaining useful life prediction to ensure reliability and safety.The IEEE standard framework for prognostics and health management is applicable to power electronic systems, emphasizing the importance of a comprehensive maintenance approach.Data preprocessing and feature mining are crucial for improving the quality of raw data, enhancing the performance of prognostics and health management applications.AI-based remaining use life prediction techniques face challenges in real-world applications, requiring quantification of uncertainty and adaptability.Power electronic systems require an adaptive maintenance strategy to bridge the gap between research and practical implementation in industry, addressing operational parameter variations. ReferenceZhao, Shuai, Frede Blaabjerg, and Huai Wang. “An Overview of Artificial Intelligence Applications for Power Electronics.” IEEE Transactions on Power Electronics 36, no. 4 (April 2021): 4633–58. https://doi.org/10.1109/tpel.2020.3024914.

Finding a reliable distributor of electronic components is critical to purchasing electronic components. In today's electronic components market, there are a large number of suppliers and product choices, so choosing a reliable distributor can ensure the acquisition of high quality components and keep the project running smoothly. Kynix, Digikey, Mouser, Newark, Arrow and LCSC are the industry's leading distributors of electronic components, offering not only a wide selection of products and a global supply network, but also competitive pricing and reliable customer service.This article introduces the benefits of Kynix, Digikey, Mouser, Newark, Arrow, and LCSC, the industry's leading electronic component distributors, to help buyers make better choices when making component purchases.Kynix: Kynix is a well-known distributor of electronic components with an extensive product line and a global supplier network, known for its wide range of products and reliable service. Kynix is committed to providing customers with high quality service and competitive prices. Kynix's prices are generally considered competitive, and they have built close partnerships with global suppliers to gain better pricing and inventory advantages. In general, Kynix has a large share in the market and is widely trusted by users.Kynix features are as follows:Strong technical support: Kynix provides users with strong technical support, including technical consultation, sample application, design support, etc. They have a professional technical team that can help users solve technical problems and provide optimized solutions.Fast purchasing process: Kynix offers a simplified and fast purchasing process. Users can easily add the desired products to their shopping cart and choose the appropriate delivery and payment method. The website also provides an order tracking function, so that users can keep abreast of the status of the order and the expected delivery time.On-time delivery: Kynix is able to process and ship orders quickly through an efficient warehousing and logistics management system and close cooperation with partners.Digikey: Digikey is one of the world's leading distributors of electronic components, known for its vast inventory and extensive product selection. Digikey works closely with a wide range of suppliers to ensure that users can find all the components they need, such as electronics, development tools and accessories. The platform has been praised for its excellent service and reliable delivery speed.Digikey features are as follows:Wide product range: Digikey offers more than 17 million electronic components, development tools and accessories. Whether it is common passive components, active components, or a variety of special sensors, modules, etc., Digikey can meet the needs of users.Diverse supplier relationships: Digikey works closely with more than 2,800 suppliers worldwide. This means that users can find products from various well-known suppliers on the Digikey platform, ensuring product quality and reliability.Global availability: Digikey has multiple logistics centers around the world to provide fast delivery services to customers worldwide.Mouser: Mouser is a highly respected global electronic component distributor. Mouser provides design tools and technical resources to assist customers in electronic design and development. The distributor is widely recognized for its extensive product catalog and commitment to customer satisfaction. Their website offers comprehensive search filters to ensure users can quickly find specific components.Mouser features are as follows:Global support centers: Mouser has support centers and warehouses located worldwide, covering multiple regions and countries including the United States, Germany, China, and Hong Kong. This enables them to provide fast and reliable logistics services, ensuring customers receive timely delivery and support on a global scale.Strong capabilities: Mouser has established solid partnerships with numerous renowned manufacturers worldwide, representing over 1,200 well-known brand manufacturers. They possess a vast inventory and offer a wide range of product categories.Excellent customer support: Mouser is known for its exceptional customer support. They provide multiple channels, including online chat, phone, and email, to address user inquiries and provide technical assistance. Additionally, Mouser offers abundant technical resources and engineering tools to support users throughout the design and procurement process. Mouser's customer service team provides round-the-clock (24/7) order processing services.Newark: Newark is a popular electronic component distributor with a long history and excellent reputation. The platform collaborates with numerous top-tier suppliers to offer a wide range of product categories. Newark emphasizes quality and reliability, striving to provide customers with outstanding delivery and support. With over 950,000 stocked products and partnerships with over 2,000 leading suppliers, Newark holds a significant market share globally.Newark features are as follows:Extensive product range: Newark offers a diverse range of electronic components from over 2,000 industry-leading manufacturers. They provide a wide selection of products covering various types, specifications, and manufacturers. Whether it's traditional electronic components or emerging technology products, Newark strives to offer diversified choices to meet customer needs.Social media presence: Newark also maintains social media pages on platforms like Twitter and Facebook to establish closer connections with customers. Through these social media platforms, customers can access the latest product information, promotions, and industry updates.Online tools and resources: Newark provides various online tools and resources such as design tools, selection guides, application notes, etc., to help users better understand and apply electronic components.Arrow: Arrow is a multinational electronic component distributor with a global supplier network and strong logistics capabilities. They provide comprehensive electronic component solutions, including analog devices, embedded systems, sensors, and wireless communication modules. Their strong technical support and global availability make them a preferred choice for many distributors. Arrow has comprehensive warehouses and value-added service centers worldwide, allowing for a flexible supply chain to better meet customer needs.One of the key features of Arrow is its extensive distributor database. As a global distributor, Arrow has established partnerships with numerous industry-leading manufacturers and suppliers, allowing them to offer customers a wide range of product choices and a reliable supply chain.LCSC: LCSC is one of the largest electronic component distributors in China. The platform collaborates with over 4,000 well-known distributors, including brands like 3M, Arduino, Intel, and more. As one of the largest electronic component distributors in China, LCSC provides a convenient platform for electronic manufacturers, engineers, and enthusiasts in China. LCSC has become an important participant in the Chinese electronic component market.One of the key features of LCSC is its global shipping and services. They have established partnerships with various international logistics companies such as DHL, FedEx, EMS, USPS, covering over 200 countries and regions.Overall, Kynix, Digikey, Mouser, Newark, Arrow, and LCSC remain top choices as leading electronic component distributors in 2024. They excel in product quality, customer service, global supply network, and on-time delivery, catering to customers of different scales and needs. Whether it's individual project developers or large corporations, these distributors can provide customers with a high-quality electronic component procurement experience.

Overview: This article explores the potential risks associated with cyber attacks on electric vehicles and provides solutions for protecting both in-vehicle and external network vulnerabilities.One of the key technologies that has helped society achieve its high decarbonization and sustainable energy targets over the last decade has been electric vehicles (EVs).What are the elements that make electric vehicles susceptible to security breaches?Efforts are being made to standardize cyber-physical interfaces for both residential and commercial electric vehicles, as these vehicles are prone to vulnerabilities and have social costs.This article examines electric vehicle vulnerabilities resulting from:In-Vehicular VulnerabilitiesController Area Network BusController Area Network (CAN) is a peer-to-peer system that works on an isolated trust model. If an attacker gets into the CAN bus or even just one electronic control unit, they can completely control how the electric vehicle works because the CAN bus security architecture is not protected against malware being put into it.To pursue a desired harmful goal, an attacker with full control could alter, eavesdrop, reverse engineer, spoof, or replay the CAN communications.Every peer that is connected to the CAN bus, such as an electronic control unit or peripheral device, receives messages sent by these devices.Furthermore, in order to minimize memory costs and ensure a prompt transfer of the information, the CAN bus message is neither authenticated nor encrypted. This is critical for time-sensitive electronic control units like the brake control unit.Sending and receiving peer IDs are not included in a message that is sent over the CAN system. Instead, it is sent according to its arbitration ID, which indicates the priority of the message. Due to its low bandwidth, the CAN bus cannot support complex and computationally demanding encryption.On-Board Diagnostic PortFrom this angle, the attacker's main task is to damage the CAN bus. The (on-board diagnostic port) OBD2 port of the CAN bus has been the focus of extensive investigation and has been designated as a critical access point to the CAN bus due to its sizable infiltration surface made possible by both physical and remote vulnerabilities.Many times during an electric vehicle's lifetime, third parties like a mechanic during vehicle maintenance, a valet while parking, and a charging station helper can physically access the OBD2 port.Furthermore, smartphone applications such as the Open Vehicle Monitoring System (OVMS) that are connected to a cellular network or a wireless short-range network can compromise the OBD2 port. Thus, the apps enable remote monitoring and management of the electric vehicle's parts and functions.There have been reports of similar vulnerabilities in FlexRay, LIN, and MOST. If the LIN and MOST were broken into, they would not allow the key attacks listed above. This is because they are not as vulnerable as the CAN and FlexRay. This is so because the LIN is less exposed to external EV networks and the MOST network is limited to non-critical ECUs like the in-vehicular infotainment system.Tire Pressure Monitoring System Another in-vehicular attack vector is the Tire Pressure Monitoring System (TPMS). The technology is susceptible to hacks, which might compromise electric vehicle security and privacy. The tire pressure sensors transmit unencrypted signals; their identification is static 32-bit strings, and their messages lack authentication.Attackers can overhear, reverse engineer, and spoof communications with an electric vehicle within 40 meters because of these security weaknesses. False data injections into the electric vehicle in-vehicular infotainment system and remote tracking of the electric vehicle are the outcomes of the attack.External Network VulnerabilitiesPhysically Accessible PortsIn addition to the OBD2 connector, there are other physical interfaces that are connected and can be utilized to control the electronic control units and external cyber layer. It includes things like USB ports, SD card ports, CD/DVD drives, headphone connectors, touchscreens, and optical media readers.For the in-vehicular infotainment system's software updates, smartphone charging, media playback, and human interface, these ports are frequently physically accessed. When malicious devices are placed into these ports, an attacker can use them to introduce persistent malware into the in-vehicular infotainment system, start a denial-of-service attack, and even act as a side-channel access point to interfere with the operation of other electronic control units.An electric vehicle may come into contact with such a malicious device at several stages of its maintenance and supply chain.Internet Service PortalsThe in-vehicular infotainment system has wireless interfaces (like Bluetooth) for interacting with cellphones in addition to USB connections. Despite being short-range, this pairing is susceptible to cyberattacks.This flaw gives an attacker the ability to infect the in-vehicular infotainment system with malware, prevent its service from working, and take control of smartphones and in-vehicular infotainment data.Malicious smartphone apps that are mirrored in the in-vehicular infotainment dashboard also present data integrity risks to the in-vehicular infotainment system and side-channel threats to the CAN bus.When electric vehicle drivers use different third-party smartphone applications for electric vehicle charging station locating and remote electric vehicle monitoring and control, these vulnerabilities probably present security problems. Moreover, third-party programs that have been installed on the in-vehicular infotainment system may be dangerous or vulnerable to attack.Electric Vehicle Charging StationAn electric vehicle typically connects to an electric vehicle charging station using a CAN bus or the Power Line Communication's wired communication layer. This communication protocol, ISO 15118, is susceptible to cyberattacks.ISO 15118 governs the connection between an electric vehicle and an electric vehicle charging station but does not include any security measures like message certification or end-to-end encryption. It could allow a remote attacker to intercept, alter, and fake the electric vehicle charging message.Radio StationsRemote cyberattacks like spoofing and jamming can affect GPS signals, allowing attackers to supply erroneous geographical information and potentially disable the navigation system in electric vehicles.Long travel distances cause the GPS signals to be relatively faint; as a result, the GPS receiver prefers the attacker-generated stronger signals. Similarly, signals sent to an electric vehicle radio by FM radio stations are susceptible to malware injection and remote spoofing attacks.Road-Side Infrastructure and VehiclesIntelligent and autonomous transportation advancements necessitate the wireless communication of vehicles. The vehicles and roadside units (RSUs) in this futuristic communication architecture, known as the vehicular ad-hoc network (VANET), are connected through LANs or cellular networks.For improved safety, comfort, and efficiency when driving and routing, vehicles communicate with roadside units and other vehicles regarding information on road conditions, traffic, accidents, and vehicle position and speed. Nevertheless, these interfaces make the vehicles' data integrity and privacy more vulnerable to attacks from other networks and devices.By imitating the presence of several virtual vehicles in the network, an attacker may, for instance, conduct a Sybil-type attack on VANET. These fake vehicles have the ability to disrupt the network or propagate false information to roadside units and other linked cars.Original Equipment Manufacturers/VendorsThe original equipment manufacturer and outside suppliers must access electronic control units to provide security patches and software updates. Traditionally, the OBD2 and USB connections have been used to connect actual dongles and USB flash drives for this purpose.These conventional techniques are therefore susceptible to supply chain and maintenance intrusions. Currently, in order to get around the obstacles and expenses related to physical delivery, OEMs and third-party providers are moving to wireless updates.Updates are provided as code or data pictures together with metadata that includes authentication information. As a result, man-in-the-middle cyberattacks, in which an attacker can remotely spy, reject, and modify the update, are possible with wireless software upgrades. An illustration of the multi-level, cyber-physical nexus of electric vehicles, electric vehicle charging stations, and the power grid is shown in Fig. 1.Fig. 1 A schematic diagram of the multi-level, cyber-physical nexus of EVs, EVCSs, and the power grid Source: IEEE AccessSummarizing the Key PointsThe article discusses vulnerabilities in the Controller Area Network bus, Tire Pressure Monitoring System, and other physically accessible ports.ReferenceAcharya, Samrat, Yury Dvorkin, Hrvoje Pandzic, and Ramesh Karri. “Cybersecurity of Smart Electric Vehicle Charging: A Power Grid Perspective.” IEEE Access 8 (2020): 214434–53. https://doi.org/10.1109/access.2020.3041074.