针对新能源重卡活塞式制动打气泵潜在故障导致制动气源失效这一重大安全隐患，文章设计并实现一种基于多源信息融合的健康度在线监测与预警系统。该系统通过集成气压、电流、电压、温度传感器与车辆 CAN 总线，实时采集气泵系统的性能参数、电气特性与工况信息。构建一个综合加权评分与趋势预测的健康度评估模型，将多维度参数计算融合为一个量化的健康度指数HI。系统根据HI 值及其下降趋势，执行从“提醒”到“紧急”的多级预警，并在危急情况下可联动车辆控制系统实施限速与辅助制动。本研究详细阐述系统架构、健康度模型的构建方法及工作流程，论证该系统能变被动报警为主动预测，显著提升商用车的主动安全性与运行可靠性。

To address the significant safety hazard of brake air source failure caused by potential faults in the piston-type air compressor of new electric heavy-duty trucks, this paper designs and implements an online health monitoring and early warning system based on multi-source information fusion. The core innovation lies in constructing a health assessment model that combines weighted scoring and trend prediction, fusing multi-dimensional parameters into a quantified Health Index (HI). Based on the HI value and its degradation trend, the system executes a multi-level warning strategy, ranging from "Reminder" to "Emergency," and can intervene with the vehicle control system to limit speed and activate auxiliary braking in critical situations. This study details the system architecture, the construction method of the health model, and the workflow, demonstrating that the system transforms passive alarms into active predictions, significantly enhancing the active safety and operational reliability of commercial vehicles.