Browse Topic: Emissions measurement
Electric vehicles present unique challenges in electromagnetic compatibility testing due to compact packaging, high-frequency switching systems. This paper presents a systematic debugging methodology for identifying radiated emission and radiated immunity issues in these EV platforms. A comprehensive approach is outlined, covering radiated emission measurement; Bulk Current Injection based immunity simulation, and near-field probing techniques. For RI evaluation, BCI testing in the 20 to 400 MHz range is used to simulate radiated threats on the vehicle's power and signal harnesses and handy transmitter near field injections for higher frequency simulation. For RE diagnosis, conducted emission measurements on vehicle harnesses are performed using current probes to capture high-frequency currents. Additionally, near-field electric probes are used at the component to identify dominant noise sources such as DC-DC converters, Motor control unit, and improperly grounded shielding. Case
Anticipated NOX emission standards will require that selective catalytic reduction (SCR) systems sustain exhaust temperatures of 200°C or higher for effective conversion performance. Maintaining these temperatures becomes challenging during low-load conditions such as idling, deceleration, and coasting, which lower exhaust heat and must be addressed in both regulatory test cycles and day-to-day operation. Cylinder deactivation (CDA) has proven effective in elevating exhaust temperatures while also reducing fuel consumption. This study investigates a flexible 6-cylinder CDA system capable of operating across any combination of fixed firing modes and dynamic skip-firing patterns, where cylinders transition between activation states nearly cycle-by-cycle. This operational flexibility extends the CDA usable range beyond prior implementations. Data was primarily collected from a test cell engine equipped with the dynamic CDA system, while a matching engine in a 2018 long-haul sleeper cab
In-Use emission compliance regulations globally mandate that machines meet emission standards in the field, beyond dyno certification. For engine manufacturers, understanding emission compliance risks early is crucial for technology selection, calibration strategies, and validation routines. This study focuses on developing analytical and statistical methods for emission compliance risk assessment using Fleet Intelligence Data, which includes high-frequency telematics data from over 500K machines, reporting more than 1000 measures at 1Hz frequency. Traditional analytical methods are inadequate for handling such big data, necessitating advanced methods. We developed data pipelines to query measures from the Enterprise Data Lake (A Structured Data storage system), address big data challenges, and ensure data quality. Regulatory requirements were translated into software logic and applied to pre-processed data for emission compliance assessment. The resulting reports provide actionable
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