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ESD Protection for Automotive Electronics
Published in Ali Emadi, Handbook of Automotive Power Electronics and Motor Drives, 2017
Electronics (other than radios) were first introduced into automobiles in the late 1950s. However, the rebirth and rapid implementation of automotive electronics in modern vehicles really came during the 1970s, mainly due to the introduction of tough governmental regulations for fuel economy and emission control as well as the emergence of low-cost solid-state electronics based on integrated circuit (IC) technologies. Modern automotive electronics can be found everywhere in automobiles, from engine control, driveline control, motion control, to instrumentation for vehicle performance monitoring and on-board diagnosis, to safety and comfort, to various in-vehicle entertainment, communication, and navigation applications. These automotive electronics applications can be roughly characterized into three categories: control, measurements, and communications. New automotive electronics applications and features emerge at a very fast speed in modern automobiles; for example, global positioning systems (GPSs) for navigation, in-motion detection for anticollision, automatic cruise control, in-vehicle theater-quality entertainment, wireless communications, and local interconnect network (LIN)-based in-vehicle networking. Today, the cost of automotive electronics might account for up to 25% of the total vehicle costs.
Trends in Automotive Communication Systems
Published in Richard Zurawski, Networked Embedded Systems, 2017
Nicolas Navet, Francoise Simonot-Lion
In the early days of automotive electronics, each new function was implemented as a stand-alone electronic control unit (ECU), which is a subsystem composed of a microcontroller and a set of sensors and actuators. This approach quickly proved to be insufficient with the need for functions to be distributed over several ECUs and the need for information exchanges among functions. For example, the vehicle speed estimated by the engine controller or by wheel rotation sensors has to be known to adapt the steering effort, to control the suspension, or simply to choose the right wiping speed.
In-Vehicle Communication Networks: A Historical Perspective and Review
Published in Richard Zurawski, Industrial Communication Technology Handbook, 2017
Nicolas Navet, Françoise Simonot-Lion
In the early days of automotive electronics, each new function was implemented as a stand-alone electronic control unit (ECU), which is a subsystem composed of a microcontroller and a set of sensors and actuators. This approach quickly proved to be insufficient with the need for functions to be distributed over several ECUs and the need for information exchanges among functions. For example, the vehicle speed estimated by the engine controller or by wheel rotation sensors has to be known in order to adapt the steering effort, to control the suspension, or simply to choose the right wiping speed. In today’s luxury cars, several thousands of signals (i.e., elementary information such as the speed of the vehicle) are exchanged by up to 100 ECUs [1]. Until the beginning of the 1990s, data were exchanged through point-to-point links between ECUs. However, this strategy, which required an amount of communication channels of the order of n2, where n is the number of ECUs (i.e., if each node is interconnected with all the others, the number of links grows in the square of n), was unable to cope with the increasing use of ECUs due to the problems of weight, cost, complexity, and reliability induced by the wires and the connectors. These issues motivated the use of networks where the communications are multiplexed over a shared medium, which consequently required defining rules—protocols—for managing communications and, in particular, for granting bus access. It was mentioned in a 1998 press release (quoted in Ref. [45]) that the replacement of a “wiring harness with LANs in the four doors of a BMW reduced the weight by 15 kg.” In the mid-1980s, the third part supplier Bosch developed controller area network (CAN), which was first integrated in Mercedes production cars in the early 1990s. CAN has become today the most widely used network in automotive systems, and already in 2004, the number of CAN nodes sold per year was estimated [38] to be around 400 millions (all application fields). Other communication networks, providing different services, are now being integrated in automotive applications. A description of the major networks is given in Section 50.2.
Simulation design for thermal model from various materials in electronic devices: A review
Published in Numerical Heat Transfer, Part A: Applications, 2022
Raihana Bahru, Mohd Faiz Muaz Ahmad Zamri, Abd Halim Shamsuddin, Mohd Ambri Mohamed
Kesarkar and Sardana [24] studied the simulations in steady-state conditions, carried out in FloTHERM™ and all three modes of heat transfer, i.e. conduction, convection (natural airflow) and radiation are considered. The ambient around the electronics is assumed to be similar to that faced by automotive electronics in the field. This study is focused on the importance of TIM by varying all three parameters, which are thickness (t), thermal conductivity (k) and cross-sectional area (A), reflect the performance of the heat sink. The observations were set in typical thickness of TIM, variation of the TIM thickness for a constant value of thermal conductivity and varied thermal conductivity of TIM. The thickness variation refers to the thermal conductivity established in the market for industrial applications. The obtained results from the analysis are assumed suitable for heat generation in the housing (contains PCB and heat-dissipating components) of 30 W. Besides, the change of heat sink materials will affect the fabrication cost, and these preliminary studies will give some early views on changing materials. They found that TIM gives a significant increase in component temperatures and sometimes, the TIM thickness is almost negligible for housing of 30 W. For a high heat-generating electronic control unit, the change of TIM thickness and thermal conductivity are important on observation.
Combining biased regression with machine learning to conduct supply chain forecasting and analytics for printing circuit board
Published in International Journal of Systems Science: Operations & Logistics, 2022
For upstream suppliers, demand uncertainties arising from downstream buyers usually result in difficulties in conducting efficient DP. For downstream buyers, seasonal variations or cyclic trends in consumer products usually lead to obstacles in accomplishing effective SF. Despite numerous techniques have been proposed, most of them have the following shortcomings (Trappey & Wu, 2008; Wang & Chen, 2019; Zhong et al., 2016): (1) Qualitative group decisions based on aggregating expert opinions make it difficult to conduct data-driven planning and forecasting. (2) The impacts of seasonal variations and demand uncertainties are not considered in scenario sensitivity analyses, and (3) The dependencies between the upstream component and the downstream products are not incorporated into the decision-making process. Consequently, a novel framework is presented to help PCB (printed circuit board) manufacturers achieve collaborative DP and SF. PCB that mechanically fastens and electrically connects electronic parts is a key component in the 5G era. PCB has wide applications, such as computer and peripherals, military and aerospace, consumer and industrial electronics, communication and mobile carriers, and automotive electronics. It is made of conductive tracks and pads etched from single or multiple layers of copper laminated onto and between sheet layers of a non-conductive substrate. In Figure 1, PCB components include the IC substrate, single/double side, multilayer rigid PCB (for desktops, laptops, servers, printers, and panel displays), flexible PCB (for bending smartphones and tablets), and microvia.
Experimental investigation on magnesium AZ31B alloy during ultrasonic vibration assisted turning process
Published in Materials and Manufacturing Processes, 2022
Magnesium alloys possess various unique properties such as low density, low melting point, low ductility, high strength-to-weight ratio, etc. They find extensive applications in various industries such as biomedical, automotive, electronics, aerospace, etc.[1–3] The functional performance of the magnesium alloys is found to be enhanced during the machining process but the selection of machining parameters is a critical factor especially during the machining of magnesium alloys.[4,5] The machining performance is generally influenced by machining parameters, machining conditions, and cutting tool parameters.[6–8] Generally, cutting fluids are used during the machining operation, leading to increased environmental pollution and production costs.[9] Additionally, cutting fluids generates harmful emissions in an open environment during the machining of magnesium alloys.[10] Therefore, hybrid machining processes are found to be eco-friendly processes and enhanced machinability is obtained than CT.[11] Among the hybrid machining processes, UVAT is one of the widely utilized hybrid machining processes.[12,13]