混合动力电动汽车中利用决策树CART算法的能源管理方案.
To solve the problem of nitrogen oxide (nox) emission of hybrid electric vehicle (HEV), a diesel hybrid energy management strategy based on decision tree CART algorithm is proposed. Firstly, a classification algorithm (Classification and Regression Tress,CART combining regression tree and decision t...
| Publicado en: | Studia Poliana no. 22; pp. 229 - 235 |
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| Formato: | Artículo |
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Studia Poliana
2020
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=142451854&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 142451854 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 11396660 8XIR jtl: Studia Poliana issn: 11396660 maglogo: N pubinfo: dt: 2020 iid: 22 pid: 94698 pub: Studia Poliana artinfo: ui: 142451854 10.16526/j.cnki.11—4762/tp.2020.02.048 ppf: 229 ppct: 6 formats: fmt: @attributes: type: P size: 6MB tig: atl: 混合动力电动汽车中利用决策树CART算法的能源管理方案. aug: au: 徐燕 affil: 四川工业科技学院智能制造与车辆工程学院,四川德阳 618500 su: Hybrid electric vehicles Energy consumption Decision trees Energy management CART algorithms sug: subj: Hybrid electric vehicles Energy consumption Decision trees Energy management CART algorithms keyword: CART (classification and regression tress) algorithm decision tree diesel hybrid electric vehicle energy management strategy predictor variable 决策树 柴油混合动力汽车 能源管理策略 预测变量 CART算法 ab: To solve the problem of nitrogen oxide (nox) emission of hybrid electric vehicle (HEV), a diesel hybrid energy management strategy based on decision tree CART algorithm is proposed. Firstly, a classification algorithm (Classification and Regression Tress,CART combining regression tree and decision tree is proposed. According to the characteristics of categories and variables, the trend relationship of each case is predicted from one or more predictive variables. Then, by controlling the torque distribution between the engine and the motor, additional degrees of freedom are introduced to adjust the optimization tradeoff from pure fuel economy to pure restriction; Finally, the simulation method based on software in the loop and hardware in the loop is adopted to understand the system performance according to the power system configuration and adjust the proposed energy management strategy. The experimental results show that the proposed diesel hybrid energy management strategy can reduce the impact on fuel consumption and limit the emission potential by selecting the best operating point and limiting engine power. Compared with other relatively new schemes, the proposed scheme has smaller emissions under the same fuel consumption, and can be significantly reduced under the condition of slightly reduced fuel consumption. 针对混合动力电动汽车(HEV)氮氧化物( )排放的问题,提出了一种基于决策树CART算法的柴油混合动力能源管理策略。首先,提出了一种结合决策树与回归树的分类算法(Classification and Regression Tress,CART),针对类别和变量特征,从一个或多个预测变量中预测出个例的趋势变化关系；然后,通过控制发动机和电动机之间的扭矩分配,引入了额外的自由度以调整从纯燃料经济性情况到纯 限制情况的优化权衡；最后,采用基于软件在环路和硬件在环仿真的方法,从而根据动力系统配置了解系统性能,并调整所提出的能源管理策略。实验结果表明,提出的柴油混合动力能源管理策略中, 的减少对燃料消耗的影响,且可以通过选择最佳工作点和限制发动机动力来限制 排放的潜力。相比其他几种较新的同类方案,提出的方案在同等燃料消耗的情况下 排放量更小,在燃料消耗略有下降的情况下,可以显着降低 。 pubtype: Academic Journal doctype: Article src: R language: Chinese refInfo: copyright: @attributes: flag: Y custom: Copyright of Studia Poliana is the property of Studia Poliana and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. item: Studia Poliana holder: Studia Poliana dt: @attributes: year: 2020 holdings: @attributes: islocal: N |
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