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Erica Zhu Feilong Jiangli

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  1. Chongqing Feilong Jiangli collects the latest information for you, so that you can get the most cutting-edge technical information. A private company focused on developing the first rechargeable lithium-metal batteries in the United States announced that it would cooperate with SKI, Korea's largest energy and chemical company, to develop lithium-metal batteries. This cooperation will focus on solid-state lithium anode laminates, which can double the energy density and cycle life of rechargeable batteries. The initial goal was to produce and test prototype batteries to prove whether the increase in volume and weight led to an increase in energy density and cycle life relative to existing lithium-ion batteries. SK Innovation plans to complete the research on conductive glass separators by the end of 2021 and apply them to the development of lithium metal batteries. Conductive glass separator is the key technology to promote the stability of lithium metal batteries. The company hopes to successfully develop conductive glass separators to accelerate the commercialization of lithium-metal batteries. A battery company based in Berkeley, California, USA, has invented and patented a technology to protect the electrodes of lithium-metal batteries, which is the core technology of sulfur-lithium batteries, lithium-air batteries and water-lithium batteries. Scientists at the battery company have invented a patented process that combines lithium metal with a continuous monolithic glass electrolyte. Battery validation in the laboratory indicates that continuous monolithic glass prevents dendrites and promotes lithium metal recycling.
  2. Chongqing Feilong Jiangli collects the latest information for you, so that you can get the most cutting-edge technical information. With the development of autopilot technology in the direction of wider application, it has made a lot of progress in imaging. However, a technical challenge associated with improving safety is the ability of a self driving vehicle to not have a strong ability to observe the surrounding corners. Imaging and sensing are the key technologies of automatic driving, and also the key areas of 3D laser scanning system, such as lidar (optical detection and ranging). Such a system allows automatic driving vehicles to detect and avoid obstacles by using rotating laser beams to drive safely. However, the current imaging technology needs to be improved in order to improve the performance of the self driving vehicle. According to foreign media reports, researchers at Boston University have conducted a study to develop a new method that allows artificial intelligence components in autonomous driving vehicles to see the corners of vehicles around the University. Researchers at Boston University have succeeded in making autonomous vehicles perceive the surrounding corners without using advanced optical devices. The technology is based on a standard digital camera and a special algorithm called "computational periscope". It works like a toy periscope, a device consisting of two mirrors or prisms that allow people to see objects blocked by obstacles. Although the technology does not rely on mirroring, the principle is similar. The algorithm developed by Boston University uses the fact that light can be reflected from structures similar to walls in different modes to assess the degree of disorder created by different objects. The main task of the AI component is to interpret the scattered reflection image.
  3. Chongqing Feilong Jiangli collects the latest information for you, so that you can get the most cutting-edge technical information. Researchers at University of Michigan, by focusing on human gait, body symmetry and foot position, use more precise technology than now to teach autopilot to identify and predict pedestrian actions. Data collected by vehicles through cameras, lidars and GPS allow researchers to capture video clips of human action and reproduce them in three-dimensional computer simulations. On this basis, scientists have created a "biomechanically inspired recurrent neural network" to classify human actions. According to the researchers, they can use the neural network to predict the movement and future position of one or more pedestrians 50 yards away from the car. If a vehicle wants to have the necessary predictive ability, the neural network needs to study the details of human movements in depth: the rhythm of human gait, the mirror image of symmetrical limbs and the way in which the position of feet affects human stability when walking. Many machine learning algorithms that upgrade the level of automatic driving to the present level involve two-dimensional images. If a computer is shown millions of pictures with parking signs, it will eventually be able to recognize them in real time. By using a few seconds of video clips, the University of Michigan system can study the first half of the video and make predictions, then confirm the predictions with the second half of the video. The research results show that this new system improves the ability of the autopilot to predict the most probable situation in the future. Finally, the system can enhance the safety of the self driving vehicle.
  4. Chongqing Feilong Jiangli latest information. In addition to the mainstream automobile manufacturers, companies that develop automated driving and networked automotive technology are also facing huge risks, and may lose key start-up funds to buy and refit cars and fail to test their software. Vehicles must be powered by wires, equipped with on-board cameras and sensors, and managed with a large number of data generated by vehicles and other technology stacks. StreetDrone calls itself "Android in the world of autopilot world", and others can build autopilot based on its operating system. Bestmile announced that it has partnered with StreetDrone, a manufacturer of Intelligent Networked Autopilot Technology. The two sides will integrate Bestmile's mobile travel service platform with StreetDrone's Xenos platform so that StreetDrone can provide a complete automobile and mobile travel service operating system. StreetDrone's Xenos platform provides hardware (including Renault Twizy car) and software combination to become the foundation of integrated technology. This technology needs to work together to make it safe and reliable. Bestmile enables StreetDrone vehicles to be used by the fleet. In addition to testing the performance of a single vehicle, it can also test scalable fleet services. Bestmile's mobile travel service platform is the industry's first such solution, allowing any brand, any kind of car to communicate and work as a member of the smart fleet. Its technology enables human-driven vehicles and self-driving vehicles to work together to provide on-demand mobile travel services through optimized allocation, route planning, coalition, energy and maintenance management. Bestmile's platform also provides advanced matching algorithms that can process travelers, vehicles and third-party data and send the right vehicles to the right place at the right time. Data intelligence and machine learning technology will improve system performance continuously. Service providers around the world can use the platform to configure service areas, define key performance indicators such as vehicle usage and waiting time, and monitor services in real time.
  5. Nowadays, more and more driver assistance systems equipped with cameras and sensors can detect objects more effectively than drivers. Moreover, speech recognition technology has already been equipped with vehicle navigation system. Traditional driver assistance system can detect objects (vehicles, pedestrians, etc.) and then inform the driver. However, sometimes drivers will be annoyed by such vague and one-way notification, which will lead to the driver taking the wrong road. In response to such restrictions, Mitsubishi Electric has developed new technologies for intelligent notification and natural navigation functions, which are expected to help make driving safer and more convenient. After identifying the direction the driver is facing, the technology uses intelligent notification to alert the driver about objects beyond the driver's sight. In addition, the HMI Natural Navigation System can respond in a natural dialogue when the driver verbally asks questions about the driving route, without pressing a button or saying an activation word. Intelligent notification function combines Mitsubishi Motor Maisart image recognition technology and vehicle video camera information to identify potential dangerous objects, such as cars, humans and other moving objects, located outside the driver's line of sight. The object facing the driver is identified by the driver monitoring system (DMS). The system monitors the driver by camera. By comparing the direction of the moving object and the direction of the driver, the blind spot of the driver is estimated. On this basis, the driver is warned by the monitor and the alarm. Tests of Mitsubishi Motor show that the system is particularly effective in detecting objects and attracting driver's attention. Natural navigation uses DMS and a series of microphones (multiple microphones that record sound simultaneously) to detect when the driver opens his mouth and to understand the driver's voice cues. It is worth noting that the system can not only recognize voice, but also distinguish the questions that the pilot wants to ask about the navigation system and other irrelevant conversations between the crew. Drivers can talk to the system in a highly natural way to provide and receive information.(Edit by Chongqing Feilong Jiangli)
  6. Amazon, an American retail giant, said on Jan. 23 that it had deployed six self-driving, pure electric vehicles to deliver goods to communities near Washington's Snohomish County. The car is the same size as a small cooler and is decorated with a Prime logo. The six round of autopilot will be driven along the delivery route at walking speed, initially accompanied by an employee. Amazon said the car was developed by its Seattle research and development laboratory to ensure safe driving around pedestrians, pets and other objects. Amazon, like several other big retailers, has begun to use driverless cars to transport groceries or other goods with the launch of the Automated Delivery Vehicle Amazon Scout. WAL-MART (Walmart) and partners Udelv, Ford and Waymo participated in several pilot projects to complete online grocery orders using autopilot cars. In December 2018, Kroger launched its first self-driving express service for the public. Last week, American snack giant Ahold Delhaize partnered with San Francisco-based Robomart to test-run driverless cars using its Stop & Shop chain.
  7. Tesla Chief Executive Elon Musk said Tesla was working to upgrade its Tesla Cam Driving Recorder, equipped with a "Sentinel Mode" to achieve 360 degree monitoring, and that the Driving Recorder would soon be on the market. Later last year, Tesla launched a traffic recorder with wireless update function, and the recorder used the camera of its automatic driving system Autopilot. In the first edition of the driving recorder equipped with this function, Tesla owners need a USB flash drive with "as much available storage space as possible" and need to format it into FAT32 file system. The driver needs to manually create a folder called "TeslaCam" and insert it into one of the front-end USB ports. Once inserted, the vehicle will identify the status bar at the top of the car and the touch screen will display the tachograph function icon. At this time, the recorder will automatically start recording, the owner can control the recorder by pressing the icon. When the function is in use, before the first recording video will cover the old one hour. If at the time of recording click on the tachograph icon, the driver can be archived for the last ten minutes of video, the video will be saved with time stamp, will not be covered. But the traffic recorder still has limitations. The driver's vision is limited to Autopilot prior to the camera. Subsequently, CEO Mask said, the future version of the tachograph use more automatic driving camera, and increase the parking mode. Now, Mask in order to realize the 360 degree monitoring of vehicles, the traffic recorder equipped with sentinel mode". But musk also pointed out that only with the "enhanced autopilot" suite will apply new vehicle driving recorder. The first edition of the TeslaCam release notes, Tesla said the new function is only applicable to 2.5 vehicles equipped with Autopilot hardware. Recently, Tesla Motors suffered a series of breaking in the event, the new function may lead to potential spoilers and thieves know crime will be recorded, so as to reduce such incidents.
  8. Warren Buffett's Berkshire Hathaway has taken steps to enter the lithium industry and negotiated to allow the extraction of lithium from the company's geothermal wells in California. According to a financing document, the joint venture hopes to produce up to 90,000 tons of lithium carbonate annually from Berkshire's Solton Lake Geothermal Power Plant, valued at about $1.5 billion (about 10.2 billion yuan) at current prices. According to people familiar with the matter, the company has been negotiating with Tesla on the supply of lithium, a key material for electric vehicle batteries. If the project is successful, it will provide reliable lithium materials for American automobile manufacturers and battery manufacturers and reduce dependence on large lithium producers in Chile and Australia. Currently, the only lithium supply in the United States comes from Yabao's Yinfeng Mine in Nevada. Solton Lake Geothermal Power Plant has the potential to become one of the largest lithium resources in the world, comparable to Leithium Triangle in Chile and Argentina. Tesla had previously been interested in the potential of Lake Solton. In 2014, Elon Musk, Tesla's chief executive, wanted to buy Simbol Materials for $325 million (2.21 billion yuan). The company had considered extracting lithium from the geothermal power plant in the region, but it rejected Tesla's acquisition. Berkshire Hathaway has reportedly been authorized to extract lithium from 10 geothermal facilities in the Salton Lake area. The company initially hoped to raise $20 million (about 140 million yuan) through private equity to grant lithium extraction rights to its new company Salton Sea Industries. The company expects that the project will eventually cost about $2.5 billion (about 17 billion yuan). But according to Reuters, Berkshire Hathaway denied the rumor. A spokesman for Berkshire-Hathaway said: "No one has yet obtained permission to extract lithium or any other mineral from a geothermal well in California."
  9. Mazda MX-5 Drop-Head Coupe will show off its new accessories at the exhibition. The car is equipped with a removable carbon fiber hard roof, which can provide users with safer protection, but the weight increase is not large. It is said that the structural rigidity of the vehicle can be improved by this structural component, but the increase will not be too large. After all, this structural component is not a fixed structural component. At present, it is not clear whether Mazda will have a soft top version of Mazda MX-5 Drop-Head Coupe, but it is expected that there will be. The Carbon Fiber Hard Top is matched with the standard Mazda MX-5 to enhance the car's appeal. It also features a 16-inch RAYS forged wheels, a new clutch and flywheel, a limited-slip differential and a more supportive Recaro seat. The Bodykit is exquisitely designed with excellent front bumpers and side skirts. Mazda MX-5 Drop-Head Coupe is a sophisticated, well-designed car, and the name "Drop-Head Coupe Concept" is also very atmospheric, complementing its new wheel and carbon fiber components.
  10. Solar Edge announced that consumers of electric vehicles (EV) can now use Google Assistant to control their solar inverters for charging electric vehicles. Solo Technologies Co., Ltd. is one of the first companies to integrate the charging function of electric vehicles with Google assistants. Solar Technologies provides the world's first solar energy inverters for charging electric vehicles. Through innovative solar boost modes, the inverters charge six times faster than standard level 1 chargers. Integrating this technology into Google Assistants can simplify the charging process of electric vehicles for consumers and meet the needs of smart energy solutions. Lior Handelsman, founder of Solo Technologies and vice president of marketing and product strategy, said: "Smart home mainly provides convenience and interconnection, but the next step for smart home is to integrate smart energy management solutions such as electric vehicle charging. By working with Google to combine the convenience of smart home with the value of smart energy, Solar Technology can enable more people to use smart solar energy and be in the leading position in this field. Now, consumers can communicate with Google assistants to start or stop charging electric vehicles. Solo Technologies also plans to add other features to Google's assistant commands, such as querying the charging status of electric vehicles, checking the average mileage that can be reached during the charging process, and booking the charging ahead of time.
  11. MINIEYE recently announced that it and Xilinx (Inc) have developed a turnkey sensing system for ADAS. The two companies are working on creating solutions for car companies and first-class suppliers, and running MINIEYE IP on Sales Zynq-7000 and Zynq UltraScale + MPSoC platforms to achieve 1-3 self-driving. According to Liu Guoqing, founder and CEO of MINIEYE, the new technology can identify and analyze more than 20 kinds of traffic targets, using the Sellings MPSoC platform. The scheme can realize signal input of cockpit exploration, target geophysical exploration and other sensors. This kind of function is designed to be applicable to complex automatic driving situations. After combining MINIEYE's algorithm with the advanced platform of Sales, the two sides hope that this scheme will help automobile companies and first-class suppliers to reduce R&D costs and improve their R&D efficiency. MINIEYE can provide high-precision deep neuron network (DNN), make full use of Sellings vehicle-grade chips, while maintaining low power consumption. MINIEYE has installed the former market products into the major mainstream automobile companies'models. This scheme can help users deploy differentiated visual algorithms. The software and hardware of Sellings on-chip system are programmable, and can be equipped with new features and functions for vehicles, aiming at meeting the NACP requirements of different countries.
  12. Farreo has developed an end-to-end learning system for speed control. The system adopts the function of neuron network and long-term memory (LSTM), which is a recurrent neural network (RNN), and can learn long-term dependencies. The new system was developed by Wirbel and her colleagues, who also deployed an artificial neural network (ANN), which relies on in-depth learning technology. The network has been provided with a large number of demonstrations of human drivers'vehicle operation, which are recorded by forward-looking cameras and can be closely related to the driver's visual field when driving. The neuron network will also be trained to imitate the driver's behavior, especially focusing on reproducing the current speed of the vehicle. For example, when the input image contains a speed-limiting panel of 50 km/h, the neuron network will ensure that the current speed of the vehicle is not higher than 50 km/h. Perhaps in the near future, the neuron network system will be deployed in the automatic driving vehicle to improve the efficiency of speed control and achieve more intuitive driving control. Researchers plan to apply this proof-of-concept to more complex driving situations, adding a variety of complex driving manipulations, such as diversion, turning at intersections or vehicle navigation at roundabouts.
  13. At the CES exhibition in 2019, Intel's subsidiary Mobileye announced that it was seeking to expand strategic cooperation with the Chinese automaker Great Wall Automobile (GMW). Mobileye is a leading supplier of Advanced Driver Assistance Systems (ADAS) and Automatic Driving (AD). As part of the partnership, Great Wall will seek to integrate Mobileye's ADAS system into its various models (L0-L2) in the next three to five years. While integrating the ADAS system, the two companies will also cooperate to develop a higher level automatic driving system (L3 and higher level) according to the unique characteristics of the Chinese road. The potential partnership with Great Wall Automobile will expand Mobileye's growing business in China, and the company's ADAS technology has maintained a good momentum in the Chinese market. With the increasing demand of automobile manufacturers for ADAS solutions and becoming a global standard requirement, Mobileye uses the large amount of data it collects from the deployed ADAS systems to enhance and achieve a higher level of automatic driving. Mobileye L0-L2 ADAS: Mobileye is the global leader in the research and development of computer vision technology for ADAS systems. Mobileye's technology, supported by its SoC product EyeQ <, can provide power for L0, L1 and L2 passive safety functions such as forward collision warning, automatic emergency braking and lane maintenance, and millions of vehicles from 25 automobile manufacturers around the world have adopted Mobileye's technology. L2 + Level: Mobileye's L2 + Level ADAS improves L1-L2 driver's auxiliary safety function and provides more convenience for drivers on today's roads. L2 + ADAS enhances the semi-automatic driving function of vehicles by using Mobile Road Experience Management (REM) map solution, and realizes self-adaptive endurance, lane maintenance assistance and other advanced functions in more complex driving scenarios such as urban environment using Roadbook () data. Although drivers of L2 + technology vehicles must be alert to confirm their actions and take over when needed, the improved functions provide great convenience and safety, while reducing the gap with higher-level automatic driving. Level 3 and Full Auto Driving: In addition to integrating ADAS and L2+, Mobileye also supports automobile manufacturers in developing higher-level auto driving, including L3 for passenger cars and L4 and L5 for fully automated vehicle fleets. The cooperation between Mobileye and Great Wall Automobile has increased Mobileye's partners in L3 systems, including BMW, Fiat-Chrysler, Ulai, Nissan and SAIC.
  14. Tesla describes the current method of detecting vehicle damage: one is to wait until a failure occurs and then replace or repair the failed components. But this method is particularly dangerous, because equipment failure may pose a security threat, or even greater threat than before dealing with equipment failure. The other is to check or replace equipment regularly (such as monthly checks or checks after a certain number of miles have been traveled). However, this method is only based on "experience" or estimation. Although frequent inspection and maintenance may prevent equipment failure due to pressure damage, this method is inefficient, and regular inspection is time-consuming and expensive. Tesla's latest patent application indicates that its research method can detect vehicles before they break down or even drive them to service centers automatically. Tesla's patent seeks to find a way to detect the "stress cycle" of certain automotive components in order to detect potential faults before they occur. Tesla also envisions a future in which vehicles can drive themselves to service centers when problems are identified. For example, the processor can send stress cycle data and damage data to the service center so that the service center can contact the driver to make an appointment for repair after confirming the damaged parts. In addition, if the vehicle is an automatic driving vehicle, it can be instructed to drive automatically to the maintenance service center for maintenance. Chongqing Feilongjiang Automobile Water Pump, Oil Level Meter, Rubber Parts, Stamping Parts.
  15. HERE Technologies announced a new partnership with Amazon, which will integrate Amazon Alexa and HERE navigation and location services. With Amazon Alexa's voice-first interaction combined with HERE's leading on-board navigation solutions, car manufacturers can easily provide intuitive voice-first experience for both internal and external users. Alexa will first be integrated into HERE's new one-stop solution Navigation On-Demand program, which enables automobile manufacturers to achieve a fully functional new navigation experience in their vehicles. With Alexa Auto tools and application interface (API), HERE creates a real voice-first automotive navigation experience that allows users to focus on the road while Alexa also provides personalized guidance when and where drivers need it most. HERE will also provide information on its location service platform and Alexa service, allowing users to search and locate points of interest, access real-time traffic information, and seamlessly plan routes inside and outside the car. For example, users can ask Alxa at home to set a reminder to buy bread at the grocery store after work. At the end of the day, the navigation system will find the best way to go to the grocery store after work based on real-time traffic information and user reminders, and remind the user to buy bread when the vehicle approaches the store. Amazon will use HERE's high-quality positioning service to enhance Alexa's positioning awareness and provide context and insights for important location data to help users estimate the time to work or to the nearest cafe. In the future, Amazon and HERE will also explore opportunities to provide additional features to automakers and their customers. For example, by integrating services created in HERE Open Location Platform (OLP) Alexa, Alexa can answer questions in a more conversational manner. At present, enterprise users use HERE's OLP platform to enrich, access their data, and contribute to the next generation of positioning services. HERE's OLP platform has acquired real-time vehicle sensor data from many automobile brands, and then converted the data from HERE into real-time world and safety information, such as traction loss or early hard braking, and transmitted to the embedded navigation system and advanced driver assistance system (ADAS) of the automobile.

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