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From OBD to connected diagnostics: a game changer at fleet, vehicle and component level ?

机译：从OBD到Connected Diagnostics：舰队，车辆和组件级别的游戏更换器 ？

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Early on-board diagnostics (OBD) standards were enforced in 1988 and, by the beginning of the XXI century, all major automotive markets require some sort of OBD. Over the years, the diagnostics software layer has grown in complexity, yet robust fault detection remains a challenging task: insufficient memory and computation power, suboptimal calibration, and the lack of sufficient real-life operation data for model development are some of the limiting factors. The connected vehicle paradigm allows a complete reshaping of the vehicle diagnostics: real-life data feeds provide operation data of the vehicle fleet; artificial intelligence assists data clustering and model development; and over-the-air update tools allow the deployment of new software components and optimized calibration. A smart combination of embedded and cloud components seems to be a major step forward for the next generation of vehicles, allowing the determination of the in-service emissions at vehicle and fleet level. While many challenges are still to be solved, connectivity offers a giant leap in the area of vehicular diagnostics.
机译：早期的诊断诊断（OBD）标准于1988年实施，并在XXI世纪初期，所有主要的汽车市场都需要某种OBD。多年来，诊断软件层已经增长了复杂性，但稳健的故障检测仍然是一个具有挑战性的任务：内存不足和计算功率，次优校准和缺乏足够的现实实际操作数据进行模型开发是一些限制因素。连接的车辆范例允许完全重塑车辆诊断：现实生活数据馈送提供车队的操作数据;人工智能有助于数据聚类和模型开发;而且，空中更新工具允许部署新的软件组件和优化的校准。嵌入式和云组件的智能组合似乎是下一代车辆前进的重大步骤，从而允许确定车辆和车队水平的可行性排放。虽然仍有许多挑战仍然可以解决，但连接性在车辆诊断区域提供了巨大的飞跃。

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