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By using the relevant theory of Markov chain, the actual driving data are compressed and reconstructed, and then the city road driving cycle is constructed based on characteristic parameters such as velocity, acceleration and gradient. In the process of constructing the driving cycle, corresponding state division principle and the evaluation criteria of characteristic parameters are designed against hybrid bus. The comparison results show that the driving cycle constructed using Markov processes can reflect the real driving characteristics on city roads. Introduction Driving cycle is a velocity-time trace that describes driving characteristics of specific vehicle in specific environment. Driving cycle has been an important parameter to estimate real-world vehicle emissions and fuel consumption which are evaluation criterions of power chain design. [1,2] When vehicle is in motion, the driver changes the output power of vehicle’s power chain and finally changes vehicle velocity. The vehicle state in the next second is only related with current road condition. Then we could say that this random variable follows Markov process. [3] Compared with traditional construction method, the Markov driving cycle method better reflects the nature of velocity change. Random selection in traditional method is substituted by selection based on Markov transition matrix, and the accuracy of construction is improved. [4] 2 The original driving data collection The required parameters of the original driving data collection are velocity, acceleration and gradient. This paper adopts the OXTS Inertial+ to measure velocity, acceleration and gradient of vehicle. These parameters are combined measured by Satellite-based Global Positioning System (GPS) and Inertial Navigation System. OXTS Inertial+ measurement accuracy is shown in table 1. Table 1Measurement accuracy of the experimental equipment Position Accuracy Velocity Accuracy Roll/Pitch Acceleration Bias Linearity Scale Factor Range 2cm 1σ 0.05 km/hRMS 0.03° 1σ 10 mm/s2 1σ 0.01% 0.1% 1σ 100 m/s2 3 Data Preprocessing The data preprocessing is consists of four steps: fragment division, state cluster division, estimation of the transition matrix and analysis of characteristic parameters. 3.1 Fragment Division The fragments, which are the minimum unit of the driving cycle construction, are divided from the original driving data according to specific rules. These fragments will be used to analyze the change regulation of velocity. 3.1.1 The selection of velocity threshold The object of this study is hybrid electric bus. The pure electric mode is often applied when the vehicle velocity is low. So if the vehicle velocity is lower than the selected velocity threshold, this International Industrial Informatics and Computer Engineering Conference (IIICEC 2015) © 2015. The authors Published by Atlantis Press 1159 sampling point should be divided into the fragment which we called “stop fragment”. Analyze all of sampling points, whose velocity is below 4Km/h, and the statistical data is shown in table 2 Table 2 Probability distribution of sampling points in low velocity velocity range(Km/h) 0~0.4 0.4~0.7 0.7~1 1~1.5 1.5~2 2~2.5 2.5~3 3~3.5 3.5~4 Probability distribution 50.01% 17.32% 9.36% 7.85% 4.70% 3.36% 2.80% 2.42% 2.20% It is obvious from table 2 that the sampling points whose velocity is less than 0.7Km/h account for 67.32% of all the sampling points. After comprehensive considered, 0.7Km/h is selected as the velocity threshold of stop fragment. 3.1.2 The selection of acceleration threshold The acceleration threshold selection is as same as the velocity threshold. When vehicle travels at a uniform velocity, the vehicle’s acceleration fluctuated in a small range. Table 3 Probability distribution of sampling points in stop fragments absolute acceleration 0~0.05 0.05~0.1 0.1~0.15 0.15~0.2 0.2~0.25 0.25~0.3 0.3~0.35 >0.35 Probability distribution 82.09% 9.92% 2.59% 1.23% 0.75% 0.60% 0.49% 2.33% As we can see from table 3, about 94.6% of accelerometer readings of the sampling points are between 0 and 0.15 when the vehicle is stationary. And it is acceptable that the acceleration threshold should be set to 0.15. 3.1.3 Basis of fragment division The basis of fragment division is shown in Fig. 1. The original test data

Driving Cycle Construction of City Road for Hybrid Bus Based on Markov Process