We consider the latter case assuming that an independent transmis sion

We consider the latter case assuming that an

This preview shows page 102 - 105 out of 121 pages.

an external input. We consider the latter case, assuming that an independent transmis- sion controller exists to select the gear based mainly on drivability considerations. The vehicle speed is considered as an external input for the energy management strategy, as is the total torque request T pwt (or power request P req ), which is gener- ated by the driver via the accelerator pedal or by the speed controller in simulation, according to the general control architecture shown in Fig. 3.2 . From ( 8.1 ), if T pwt and the gear index i tr are imposed, the gearbox input torque is determined as T gb = T eng + T mot = T pwt g tr ( i tr ) · g fd . (8.4)
Image of page 102
8.2 Parallel Architecture 93 As discussed in Sect. 3.4 , the standard degree of freedom for the optimization problem is the battery power P batt . It is directly and bi-univocally related to the motor torque, T mot , because the motor speed is imposed by external inputs and the motor efficiency only depends on torque and speed (neglecting temperature effects). This allows using the motor torque as the control variable, which is more immediate for this powertrain architecture: in fact, given the torque of the electric motor, the engine torque is found by difference from T gb : T eng = T gb T mot . (8.5) The fuel power (proportional to the fuel consumption) is computed using the map in Fig. 8.2 , so it is a function of engine speed and torque. Through ( 8.2 ) and ( 8.5 ), it is computed as a function of vehicle speed, total torque request, and motor torque as P fuel = Q lhv ˙ m f ( T eng , ω eng ) = P fuel ( T gb , T mot , v veh ). (8.6) System dynamics . The system dynamic equation represents the evolution of the battery state of charge as a function of the state itself and of the control input T mot (or P batt , for what said earlier). According to ( 2.37 ), the state of charge variation is ˙ SOC = − 1 η sign ( I ( t )) coul Q nom V oc ( SOC ) 2 R 0 ( SOC ) V oc ( SOC ) 2 R 0 ( SOC ) 2 P batt R 0 ( SOC ) (8.7) with the battery parameters V oc ( SOC ) and R 0 ( SOC ) shown in Fig. 8.4 . It turns out it is more practical to use the electrochemical energy variation in place of state of charge as state in this case. According to the formulation introduced in Sect. 5.3.1 : E ech = E batt · ( SOC ( t 0 ) SOC ( t ) ) (8.8) with E batt = V oc , nom Q nom η coul ; the system dynamic equation is ˙ E ech = P ech = − E batt ˙ SOC . (8.9) The battery power is P batt = P em , e ( T mot , ω mot ), (8.10) where P em , e ( T mot , ω mot ) is the electrical power required by the electric machine to produce the torque T mot , at the speed ω mot (which is a function of the vehicle speed via the gearbox ratio i tr ). Therefore the state equation is a function only of SOC and P batt , which in turn depends on the control input T mot , and the external inputs v veh , i tr .
Image of page 103
94 8 Case Studies Control constraints . The value of engine and motor torque must remain within their respective limitations: T mot , min mot ) T mot T mot , max mot ), (8.11) T ice , min eng ) T eng T ice , max eng ), (8.12) and, in addition, the motor power is saturated according to the minimum and maxi- mum available electric power 2 : P batt , min ( SOC ) P mot , e P batt , max ( SOC ), (8.13)
Image of page 104
Image of page 105

You've reached the end of your free preview.

Want to read all 121 pages?

  • Fall '19
  • Internal combustion engine, Electric vehicle, Plug-in hybrid, Hybrid vehicle, HYBRID ELECTRIC

  • Left Quote Icon

    Student Picture

  • Left Quote Icon

    Student Picture

  • Left Quote Icon

    Student Picture