Development of a Representative EV Urban Driving Cycle Based on a k-Means and SVM Hybrid Clustering Algorithm

Abstract

This paper proposes a scientific and systematic methodology for the development of a representative electric vehicle (EV) urban driving cycle. The methodology mainly includes three tasks: test route selection and data collection, data processing, and driving cycle construction. A test route is designed according to the overall topological structure of the urban roads and traffic flow survey results. The driving pattern data are collected using a hybrid method of on-board measurement method and chase car method. Principal component analysis (PCA) is used to reduce the dimensionality of the characteristic parameters. The driving segments are classified using a hybrid k-means and support vector machine (SVM) clustering algorithm. Scientific assessment criteria are studied to select the most representative driving cycle from multiple candidate driving cycles. Finally, the characteristic parameters of the Xi’an EV urban driving cycle, international standard driving cycles, and other city driving cycles are compared and analyzed. The results indicate that the Xi’an EV urban driving cycle reflects more aggressive driving characteristics than the other cycles.

Integrated Component Optimization and Energy Management for Plug-In Hybrid Electric Buses

“…Moreover, the road slope is neglected in the synthesis process of the driving cycle, due to the road slope of the researched bus route being within ±0.01 • . The detailed process of synthesizing a typical driving cycle with the PCA and k-means clustering method can be found in Reference [43]. The driving segment is partitioned by a microtrip method from the historical driving data, and a principal component analysis (PCA) together with a k-means clustering method is employed to synthesize a driving cycle [43].…”

“…The detailed process of synthesizing a typical driving cycle with the PCA and k-means clustering method can be found in Reference [43]. The driving segment is partitioned by a microtrip method from the historical driving data, and a principal component analysis (PCA) together with a k-means clustering method is employed to synthesize a driving cycle [43]. As shown in Figure 3, the main process of the driving cycle synthesis can be summarized as three steps.…”

“…Moreover, the road slope is neglected in the synthesis process of the driving cycle, due to the road slope of the researched bus route being within ±0.01°. The detailed process of synthesizing a typical driving cycle with the PCA and k-means clustering method can be found in Reference [43].…”

Coordinated Stability Control Strategy for Intelligent Electric Vehicles Using Vague Set Theory

“…A slip rate control method based on the antilock braking system (ABS) and traction control system (TCS) is utilized to improve stability performance by effectively reducing the slip ratio of the wheels with different adhesion coefficient. Vehicle stability control effect is verified through the hardware-in-loop simulation and experiment [32].…”

Parameter Identification and State of Charge Estimation of NMC Cells Based on Improved Ant Lion Optimizer

“…With the increasingly serious problems of global energy crisis and environmental pollution, electric vehicles (EVs) have experienced explosive development and drawn increasing attention from institute and industry in the last decade [1][2][3]. The energy storage system is the most important part in EVs which is often comprised by different kinds of batteries, including lead-acid batteries, nickel-hydrogen batteries, and secondary lithium batteries.…”