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For the regenerative braking systems of electric vehicles, the corresponding regenerative braking control strategy might be designed according to the different braking intentions of the driver, so as to improve the safety, comfort and economy effectively during the vehicle braking processes. Accurate and fast recognition of driver's braking intentions was the basis of designing control strategy. An on-line recognition method of driver braking intentions was designed based on ABC-SVM algorithm and implemented to identify the driver's braking intentions accurately and quickly for the electric vehicles with brake-by-wire. Firstly, the braking data were preprocessed, and the effective features were selected by NCA feature selection algorithm, and then the braking intention recognition model was established by the ABC-SVM algorithm, and on-line recognition was carried out finally. Offline verification and online test results show that the NCA algorithm may effectively filter out irrelevant features caused by signal noise. Compared with the fuzzy reasoning, back propagation (BP), particle swarm optimization support vector machine (PSO-SVM) and genetic algorithm support vector machine (GA-SVM) recognition algorithms, the ABC-SVM algorithm may identify drivers braking intentions more accurately and quickly. [ABSTRACT FROM AUTHOR]

Hydrocarbon fuels are mainly composed of n -alkenes, iso-alkanes, cycloalkanes (primarily single-and double-ring), alkylbenzenes, indans, tetralins, naphthalene, and alkylnaphthalenes. Different hydrocarbon classes impart different properties to a fuel. An identification method of hydrocarbon classes in kerosene-based endothermic hydrocarbon fuel was established using comprehensive two-dimensional gas chromatography coupled to mass spectrometry (GC×GC-MS). Moreover, the corresponding quantitative determination was achieved using the effective carbon number correction factors of GC×GC-FID. The effects of the main chromatographic conditions such as the column system, program heating conditions, and modulation period on the separation of fuels were discussed. Nine hydrocarbon fuels were analyzed. The results showed that the contents of paraffin and cycloalkanes are consistent with the results obtained using the standard test method ASTM D2425. The relative error is within ±10%. The carbon content calculated using this method has an error of less than 0.5% compared with the elemental analysis method. This method does not require complicated pretreatment, and the sample can be injected directly after dilution. Compared with the traditional GC-MS, the operation is simple, and the differences among various samples can be observed intuitively, which helps in improving the performance of the fuel.

As coking precursors, aromatic hydrocarbons have an effect on the cracking stability of fuels. A method for identifying and quantitating aromatics in the supercritical cracking products of jet fuel was established by comprehensive two-dimensional gas chromatography coupled with mass spectrometry (GC×GC-MS). The effects of main chromatographic conditions such as initial oven temperature and modulation period on the separation of supercritical cracking products were studied. The method has good separation ability for polycyclic aromatic hydrocarbons (PAH) isomers. A total of 27 aromatics, including monocyclic aromatic hydrocarbons, bicyclic aromatic hydrocarbons, tricyclic aromatic hydrocarbons, tetracyclic aromatic hydrocarbons, etc., were identified based on standard mass spectra, the retention times of standards and literature reports. Moreover, the corresponding quantitative determination was achieved by external standard method of GC×GC-FID. The results showed that the contents of aromatics increased with the increase of gas yield. When gas yield reached 22%, the bicyclic aromatic hydrocarbons began to produce, and their contents increased exponentially with the increase of gas yield. Compared with the traditional GC-MS, the method has better separation and qualitative ability, and can be applied to the separation of complex samples and qualitative and quantitative analyses of cracking products.