Electric Multi-Objective Optimal Control Strategy for Plug-in Diesel Engine Hybrid Electric Vehicle During Engine Cold Start
The trade-off between the high NO<italic><sub>x</sub></italic> catalytical efficiency and low NH<sub>3</sub> leakage are difficult to tackle， especially during engine cold start of plug-in diesel engine hybrid electric vehicle. The NH<sub>3</sub> desor...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | zho |
| Published: |
Editorial Office of Journal of Mechanical Transmission
2020-02-01
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| Series: | Jixie chuandong |
| Subjects: | |
| Online Access: | http://www.jxcd.net.cn/thesisDetails#10.16578/j.issn.1004.2539.2020.02.005 |
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| Summary: | The trade-off between the high NO<italic><sub>x</sub></italic> catalytical efficiency and low NH<sub>3</sub> leakage are difficult to tackle， especially during engine cold start of plug-in diesel engine hybrid electric vehicle. The NH<sub>3</sub> desorption rate model， SCR temperature model and dynamic response model are established based on SCR reaction mechanism. According to Pontryagin's minimum principle， the shortest light-off time control strategy of SCR and the multi-objective integrated optimization control strategy of fuel consumption and emissions where SOC and SCR temperature designated as state variables are proposed. The simulation results from shortest light-off time control strategy show that ammonia storage capacity is apt to exceed the limit of ammonia storage capacity during the process of rapid heating. The resultant peak concentration of ammonia leakage is 4.362×10<sup>-5</sup>. By comparison， the multi-objective integrated optimization control strategy for fuel consumption and emissions can not only achieve rapid light-of but also reduce the peak concentration of ammonia leakage to 2.122 6×10<sup>-5</sup>. Meanwhile fuel economy is improved by 7.13%. Finally， the hardware-in-loop experiment based on dSPACE real-time simulation platform is implemented to validate the real-time performance and effectiveness of the proposed control strategy. |
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| ISSN: | 1004-2539 |