NOx Virtual Prediction Technology of Diesel Engine Based on HPO-LSTM

PAN Hengbin; GUAN Wei; PAN Mingzhang; LIANG Ke; WEN Tao; JIANG Shujun

Vehicle Engine ›› 2024, Vol. 0 ›› Issue (1) : 67-75.

NO_x Virtual Prediction Technology of Diesel Engine Based on HPO-LSTM

PAN Hengbin¹,GUAN Wei¹,PAN Mingzhang¹,LIANG Ke¹,WEN Tao¹,JIANG Shujun²

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Abstract

In the face of strict emission regulations, the diesel engine posttreatment system plays an immeasurable role, and the acquisition of NOx emissions is one of the prerequisites for the normal operation of SCR device in the posttreatment system. A virtual prediction model that used hunterprey optimization(HPO) algorithm to optimize long short term memory(LSTM) network was established to accurately predict NO_x emissions of diesel engine in place of existing physical sensors or as a parallel device to monitor their operation. The test was carried out on a dynamometer of diesel engine. During the highly transient operation cycle of diesel engine, several parameters that were easy to obtain and closely related to NO_x formation were input into the model. The results show that, compared with the prediction results of nonoptimized network, RMSE increases by 29.1% and 23.4%， and R² is greater than and close to 0.95 respectively when the optimized network is applied to the test set or to a new unknown transient condition. The prediction results show a highly identical trend with the measured values of sensor, which meets the requirements of onboard application and accuracy and hence verifies the feasibility of this method.

Key words

diesel engine / NO_x / prediction / hunterprey optimization algorithm / long short term memory network

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PAN Hengbin,GUAN Wei,PAN Mingzhang,LIANG Ke,WEN Tao,JIANG Shujun. NO_x Virtual Prediction Technology of Diesel Engine Based on HPO-LSTM[J]. Vehicle Engine. 2024, 0(1): 67-75