Truck & Off-Highway Engineering - April 2021 - 19

POWERTRAIN FEATURE

Supervisory
Controller

DRIVER

ECU

Calculations
_RLTs

TCU
Clutch
Engager-1

Clutch
Engager-1

Engine_ISB6.7

Transmission
_A2000

EMInertia-1

BMS

BATTERY

Tire-Rear-R
VEHICLE
Signals-FR

Brake-FR
Axle-FR

MotorGenerator_
Unit-1

VEHICLE
Signals-RR

Brake-RR
Axle-RR

EMInertiaMotorGear
Reduction-2

EMInertia-2

EMInertia

Clutch-1-1

Tire-Front-R

Brake_
Controller

Figure 2. Schematic
of the modified
GT-SUITE model
with the motorgenerator unit
connected at
different locations
depending upon
the parallel hybrid
architecture under
consideration.

ComPart_36_Driveshaft

Ambient

VEHICLE

Hybrid powertrain modules added
to develop P1, P2, P3 and P4
parallel hybrid models

MotorGenerator_
Unit

Vehicle

Differential

EMinertia

EMInertiaMotorGear
Reduction-1

Road

Axle-FL Brake-FL

VEHICLE
Signals-FL

VEHICLE
Signals-RL

Brake-RL Axle-RL

Tire-Front-L

Tire-Rear-L

MotorGenerator_
Unit

PARAMETER

FUNCTION

PARAMETERS

FULL HYBRID
RANGE

MILD HYBRID
RANGE

Battery Cost

$331/kWh

Moter Generator Cost

$7.9/kW

MG Peak Torque

50-500 Nm

20-180 NM

Power Electronics Cost

$9.9/kW

MG Maximum Speed

2,000-20,000 rpm 2,000-20,000 rpm

12.8 kg/kWh

Battery Voltage

Battery Weight

150-760V

48V

Motor-Generator + Power
Electronics Weight

Battery Capacity

20-100 Ah

10-100 Ah

0.15 kg/kW

Motor Gear Ratio

1-8

Table 1. Added cost and weight functions considered in the
model for DoE optimization.

Table 2. Parameters used for DoE study.

motor-generators were directly coupled to the front
axle of the vehicle. Again, a starter motor was included for engine starting. The P4 architecture allowed
for four-wheel-drive capability.
Axial-type permanent-magnet BLDC (brushless direct current) technology was selected for the motorgenerator due to its high efficiency, higher torque output and packaging advantage. A map-based motorgenerator model was developed with specified maximum and minimum torque curves and combined motor-inverter efficiency. Maximum motor-generator
torque during charge (1C) and discharge (3C) operation were also limited by battery capacity. Efficiency
values for the motor maps were scaled using global
factors based on operating voltage and motor-generator maximum speed. The scaling factors were derived
from measured data from different axial BLDC motorgenerators operated at different voltage levels and
maximum speeds.
The NMC battery technology was chosen for this application due to its higher specific capacity. A Thevenin
electrical-equivalent circuit-based battery cell was modeled by specifying the open-circuit voltage, series internal resistance and RC branches to model the electro-

chemical dynamics. Battery cell state of charge (SOC) also was modeled
using the default approach available within GT-SUITE.
Battery cells were arranged in series and parallel to vary battery
voltage and capacity. Battery cooling and cell balancing were not
considered in this study; however, a battery management system was
introduced to restrict battery terminal voltage and current to their
acceptable hardware limits. In addition, a cell aging model was implemented to predict battery capacity deterioration over time, based
on depth of discharge, average voltage and current.
A constrained on-off control strategy was selected for parallel hybrid powertrain management. The control strategy determines the
power split between engine and motor-generator based on the
torque demand and battery SOC. A rule-based control strategy was
selected over model-based optimization strategies, such as equivalent charge minimization strategy, due to the computational limits of
the engine control unit. Hysteresis loops were also implemented to
prevent frequent engine start-stops between various control modes.

TRUCK & OFF-HIGHWAY ENGINEERING

Results of DoE analysis
The optimization for each hybrid configuration was carried out on the
ARB transient cycle. A five-variable DoE (design of experiments) was conducted for each parallel hybrid configuration at two different voltage levels (see Table 2). The results were optimized using the FEV xCAL DoE tool.
April 2021 19

Truck & Off-Highway Engineering - April 2021

Table of Contents for the Digital Edition of Truck & Off-Highway Engineering - April 2021