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مقایسه عملکرد الگوریتم‌های ماشین بردار پشتیبان و میانگین کی در استخراج چرخه واقعی رانندگی ترکیبی تهران- آمل | ||
| نشریه مهندسی مکانیک امیرکبیر | ||
| مقاله 15، دوره 53، شماره 9، آذر 1400، صفحه 5017-5036 اصل مقاله (2.26 M) | ||
| نوع مقاله: مقاله پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22060/mej.2021.19222.6980 | ||
| نویسندگان | ||
| تابان مهر قرائتی1؛ علی مومنی موحد1؛ محمد آزادی* 2؛ سید اشکان موسویان3 | ||
| 1دپارتمان مهندسی مکانیک، دانشکده فنی و مهندسی، دانشگاه بین‌المللی امام خمینی، قزوین، ایران | ||
| 2سمنان-مهندسی مکانیک | ||
| 3دانشکده فنی کشاورزی شهریار، دانشگاه فنی و حرفه‌ای | ||
| چکیده | ||
| چرخه‌‌های رانندگی داده‌‌هایی بر حسب سرعت و زمان هستند که از آن‌ها در طراحی خودروها، مدیریت حمل و نقل و سوخت، تبیین و بهسازی شاخص‌های استاندارد استفاده می‌شود. در این پژوهش، چهار چرخه رانندگی ترکیبی بر اساس داده‌‌های واقعی استخراج گردید. برای رسیدن به این هدف، داده‌برداری با استفاده از یک خودروی سواری با موتور بنزین‌سوز به روش تعقیب خودرو، در مسیری از تهران به آمل، تحت شرایط رانندگی واقعی انجام شد. پس از آن در نرم‌افزار متلب، با استفاده از الگوریتم‌های ماشین بردار پشتیبان و میانگین کی و با در نظر گرفتن مقادیر میان‌برد و میانگین به عنوان مراکز دسته‌ها، یک کد برای تولید چرخه‌‌های مورد نظر، و محاسبه پارامترهای مشخصه‌ی آن‌ها، نظیر سرعت متوسط، درصد زمان پیمایش خودرو در حالت‌های درجا، بدون شتاب، شتابگیری مثبت و منفی ایجاد شد. سپس این چرخه‌‌ها بر اساس میانگین خطای نسبی، خطای ریشه میانگین مربع و آزمون مربع چی با یکدیگر مورد مقایسه قرار گرفتند. نتایج نشان داد اگرچه، چرخه‌‌های استخراج شده توسط ماشین بردار پشتیبان به بازه زمانی مجاز (کمتر از 1800 ثانیه) نزدیک‌ترند، اما چرخه استخراج شده توسط الگوریتم میانگین کی و میانگین به عنوان مراکز دسته‌های ایجاد شده، کمترین خطاها را ثبت نموده است. این چرخه علاوه بر آن‌که بیشتر زمان خود را در حال حرکت شتابدار بوده است، دامنه نوسانات شتابی وسرعتی بیشتری را نسبت به دیگر چرخه‌‌های مورد مقایسه گزارش نمود. | ||
| کلیدواژه‌ها | ||
| چرخه رانندگی؛ ماشین بردار پشتیبان؛ الگوریتم میانگین کی؛ چرخه ترکیبی؛ دسته‌بندی و طبقه‌بندی | ||
| عنوان مقاله [English] | ||
| Comparison of Support Vector Machine and K-Means Algorithms Performance in Extracting the Real Driving Cycle of Combined Tehran-Amol | ||
| نویسندگان [English] | ||
| Tabanmehr Qaraati1؛ Ali Momeni Movahed1؛ Mohammad Azadi2؛ Seyed Ashkan Moosavian3 | ||
| 1Department of Mechanical Engineering, Faculty of Technical and Engineering, Imam Khomeini International University, Qazvin, Iran | ||
| 2سمنان-مهندسی مکانیک | ||
| 3Shahriyar Faculty, Technical and Vocational University | ||
| چکیده [English] | ||
| Driving cycles represent the vehicle speed as a function of time and are used in vehicle design, fuel management, and the improvement of standard indicators. In this study, four combined driving cycles were extracted using real data. The data was collected from a passenger car with a gasoline engine under real driving conditions while driven from Tehran to Amol based on the car chasing method. A code was generated in MATLAB software to create the desired cycle using support vector machine and K-means algorithms considering mid-range and mean values as group centers. The characteristic parameters of the cycles such as the average speed and the percentage of the car travel time at idle, cruise, accelerating, and decelerating conditions were also calculated. These cycles were compared based on the mean relative error, the root-mean-square error, and the Chi-square test. The results showed that the cycles extracted by the support vector machine were closer to the allowable time interval (less than 1800 seconds); however, the cycle extracted by the K-means algorithm with the mean value as the centers of the generated categories, recorded the least errors. This cycle, in addition to spending most of its time in accelerated motion, represented a greater amplitude of acceleration and velocity fluctuations than other cycles. | ||
| کلیدواژه‌ها [English] | ||
| Driving cycle, Support vector machine, K-means algorithm, Combined cycle, Classification, and clustering | ||
| مراجع | ||
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