Page 291 - Distributed model predictive control for plant-wide systems

High-Speed Train Control with Distributed Predictive Control 265

320 CRH1 Traction
300 CRH5 Traction
EMU Traction (kN), Resistance (kN) 220 CRH2-300 CRH3 Traction CRH2-300
280
260
240

200
180
Traction
160
Resistance
140
120
CRH2 Traction
100
80
60
40
20 CRH5 Resistance CRH1 Resistance CRH3
Resistance
CRH1 Resistance
0
0 20 40 60 80 100 120 140 160 180 200 220 240 260 280 300 320 340
. –1
Train Speed (Km h )
Figure 12.1 Traction characteristics of the CRH2 [140]

where w is the basic resistance of EMUs (N/kN), v is the velocity of the EMUs (km/h), c ,
0 0
c , c are the empirical constants, respectively, which are correlated with the type of the EMUs.
1 2
The second order of (12.1) represents the aerodynamic drag. The rest two parts are considered
to be rolling and mechanical resistance
1
c = S C (12.2)
2
i i
2
where is the air density, S is the biggest cross-sectional area of a train, and C is the aero-
i
i
dynamic drag coefficient.
Aerodynamic drag coefficient c is made up with head coach, middle coaches, and the last
i
coach
n
∑
C = C (12.3)
i ix
x=1
where C the xth coach aerodynamic drag coefficient and n is the number of cars. According
ix
to the book by Tian [136], we can get coefficients of different group organizations as shown
in Table 12.1.
From Table 12.1, we can see that different coach has different aerodynamic resistance. The
head coach and the last coach take the most part of the aerodynamic resistance of a whole
train. In the multimass model, we must use different coefficients respectively.

12.3.1.3 The Brake of EMUs
The brake of EMUs is an external controlled force which is opposite to its current direction.
Based on different generating mechanisms, the brake includes friction brake, power brake, and