Development method of American heavy vehicle low-load test cycle

Abstract

Heavy vehicles have higher driving time and NOx emission level under low-load scenarios. Developing and inducting corresponding test cycle into emission valuation and certification standards is an effective method to improve translation from test emission results to real-world emission control benefits. At present, China is short of systematic research and achievements in this field. Present certification cycle failed to evaluate low-load emission. In America, CARB firstly applied least-square method to fit the multi-modal normal distribution with moving window average load, thus defined low-load data set. Secondly, applied K-means clustering method to classify and identity typical low-load driving scenarios. Thirdly, applied model to translate vehicle profile to construct low-load profile library. Finally, selected and combined representative profiles to construct the Low-load test cycle (LLC). Further more, by engine dynamo meter test and model simulation, LLC was used to evaluate the after treatment system and improve emission control technology under low-load scenarios. This paper comprehensively studied the overall process of cycle construction, verification and application, explained in detail the technical details of cycle construction routine, thus, provided practical technical support for development of China’s low-load test cycle.