This document describes the development of an electronic control unit (ECU) model for a hybrid electric vehicle powertrain using AMESim simulation software. The model divides torque between an internal combustion engine and electric motor based on optimization strategies to maximize fuel efficiency. Simulation results show the engine and motor speeds over various drive cycles and validate the model by achieving a higher estimated highway fuel economy than a Honda Insight vehicle with a similar powertrain architecture. The ECU model provides efficient control of the engine operating mode, torque splitting between components, throttle position, and other parameters to improve the vehicle's fuel consumption and emissions performance.

1. Development of Electronic Control Unit for a
Hybrid Electric Vehicle Using AMESim
Nihal Sanjay Pol ; Prof. Ashok B.
Thermal and Automotive Engineering Division,
School of Mechanical Engineering, VIT University,
Vellore - 632014, TamilNadu, India
nihalpol1993@gmail.com
I. ABSTRACT
A function modularization control system is
established for the vehicle with a parallel
hybrid power-train structure consisting of IC
engine with manual gearbox, electric motor.
The key objective is to increase the mileage of
vehicle in comparison with Honda Insight EX
car as the powertrain architecture is similar.
Rule based strategy is designed using power
follower model in which toque divide is key
feature. Control strategies are based on
optimization of IC engine and electric motor
performance.
For modelling this system “LMS Imagine Lab
AMESim Student Edition” software is used
which can be further used for simulation
purpose also. Various performance
parameters are studied and compared with
“AMESim Rev 13” standard model.
II. KEYWORDS
ECU, Control Strategies, HEV, AMESim,
Modelling and Simulation, Honda Insight.
III. INTRODUCTION
Hybrid vehicles are the future of automotive
industry. In need of increasing the overall
efficiency and reducing the fuel consumption and
emission, researchers have done lot of work in
field of hybrid vehicles. Depletion of crude oil
resources and emission issues have became
significant problem all over the globe. This
intends to introduce new technology for a
sustainable future. The most desired is property is
the fuel economy improvement. By optimising
the fuel economy, reduction in crude oil import
can be lowered. In order to achieve this so far
most convincing technology is hybrid vehicles. In
comparison with conventional fossil fuel vehicle
hybrid uses battery and motor/generator to
increase the fuel economy. Hybrid vehicle
consists of various components and systems in its
powertrain such as internal combustion engines,
electric motor, battery, power splitting gearbox,
intermediate clutches, etc. This project
incorporates Electronic Control Unit (ECU)
network which could be understood by observing
the model created in AMESim using the
components available in library.
IV. HYBRID ELECTRIC VEHICLE
(HEV)
In HEV both internal combustion engine (ICE)
and electric motor deliver power to wheels
following the commands of Electronic Control
Unit (ECU) to get optimum traction with less fuel
consumption. The function of intermediate clutch

2. is to connect and disconnect the ICE to
transmission. The motor cannot be used as
generator when the power output of the ICE is
greater than required to drive vehicle. In this
model the Regenerative braking technology is not
considered. HEV has advantage as power losses
in transmission are less because there is no
intermediate conversion of energy and motor or
engine directly supplies power to wheels.
V. MAJOR FUNCTIONS of ECU in
HEV
 To maximize the fuel economy
For each litre of petrol ECU will try to get
maximum mileage to reduce the running cost of
vehicle. This is done with help of maximum use
of motor torque and minimum use of ICE.
Another way is to operate the ICE in maximum
efficiency region i.e. at high torque application,
whereas the motor provides uniform toque at low
speeds [1].
 Monitoring battery State of charge
For maximising the life of battery usage of
battery potential must be in prescribed limits.
Overcharging, complete discharge and high
discharge rate should be avoided. Hence battery
management is necessary.
 Actuation of clutch
There are two occasions where clutch operation is
required. One at the time of gear shifting and
another at time when engine is running in idle
mode while motor provide the torque.
 Splitting the torque demand
For achieving high efficiency motor and ICE
should be operated at optimum region with
performance without any losses. This is carried
out by dividing the torque into Motor torque and
ICE torque command. This gives the good
control over smooth operation and higher
mileage.
 Deciding the mode for ICE
There are five operation modes in ICE namely
starting, idle, engine brake, cruising, and
maximum speed mode. Selection of mode
decides the torque output and fuel consumption
of ICE. Hence proper selection is important.
VI. MODES of OPERATION
 Green Mode
In this mode charge of battery is high i.e. greater
than 80%. All torque demand is fulfilled by
motor only whereas engine runs in idle mode.
 Blue Mode
Battery SOC is in between 40 to 80 %. Torque
demand is shared by both motor and ICE
depending upon torque split. Battery SOC,
Accelerator peddle position and torque demand
are evaluated in real time for accurate torque
divide
 Red Mode
Battery SOC is less than 40%. Hence use of
battery may lead to reduction in life. Therefore all
torque demand is fulfilled by the ICE.
Modelling of ECU
VII. Control Area Network (CAN)
The CAN is a fast and high data transfer rate
network enabling communication between ECU
and actuators. In CAN data can be updated every
10ms. All information coming from the various
sensors of the model is added to a data BUS [3].
For this model inputs for CAN BUS (figure 1)
are Clutch position, Vehicle Key position, Mass
flow rate of air, cooling water temperature,
BMEP, Engine speed. Output to actuators are

3. Throttle angle position, starter motor command,
idle valve control, start of injection command,
spark advance, Injection timing, Maximum lifts
of inlet and exhaust valve [3].
Figure 1 CAN BUS and ECU
VIII. Hybrid Strategy Control
This model can be termed as Torque Divide
because main objective is to give torque to motor
and engine according to Hybrid rules and
optimized inputs for efficient working of
components. Logic diagram for strategy used in
this model can be understood from figure no. In
logic diagram Battery SOC and Torque demand
are the inputs whereas two separate torque
outputs to motor and ICE are derived.
The load is function of the acceleration pedal
position and the determination of the idle speed
value and FMEP is function of the cooling water
temperature and idle engine speed map [3].
Idle speed = (1200 – 5 * cooling water
temperature)......(from US 6109236 A)
f(FMEP) = (cooling water temperature, engine
idle speed)
Idle torque is calculated using the frictional mean
effective pressure (FMEP) and cylinder
displacement (Vd) using formula
FMEP =
2πNTQidle
𝑉𝑑
TQmax is derived from data file provided by
manufacturer. This is used for wide open throttle
operation of engine for maximum power. This
also aid the motor by providing the uniform
torque command because the torque divide logic
only gives initial torque demand. For this model
the TQmax is calculated from Map shown in
figure 2.
Figure 2 TQmax Map
The load ([0-1]) multiplied by the maximum
torque gives a value of reference of indicated
torque. The final indicated torque reference is
computed with 3 signals : TQmax, TQind and
TQidle.
Figure 3 shows the actual logical control circuit
for the Hybrid strategy control. Maximum torque
is calculated for set of engine speeds in order to
operate the ICE in wide open throttle condition.
This is values are stored in the Map shown in
figure 2.

4. Figure 3 Hybrid Strategy Control
At zero load engine runs at idle mode and motor
is not running. As the accelerator pedal
depression increases i.e. load requirement
increases. The model is designed such that
Engine remains in idle mode up to 30% of
maximum accelerator pedal depression and motor
is providing the all required torque considering
the battery SOC is more than 40%. If the Battery
SOC is less than 40% ICE will start
unconditionally to fulfil the torque demand.
Whole strategy is based on simple logics which
decide the state of operation. For calculating ICE
torque demand when battery SOC is less than
80% and torque demand is more than 40Nm the
logic works as follows,
f(x,y)=(x==1)*y+(x!=1)*TQidle
Where, x = binary input from comparator which
checks the torque demand above 40Nm.
Y = Torque demand and TQidle = Idle torque
When x = 1 output is y and when x = 0 output is
TQidle
Similarly other logics are resolved to get the
respective torque demands. Working of model at
various torque demand and SOC status is as
shown in table 1.
Table 1 SOC and Torque demand for respective torque divide
Battery
SOC
Torque
demand
Motor torque Engine
torque
SOC
>80%
TQreq
<40 Nm
All torque
demand
Idle torque
TQreq
>40 Nm
All torque
demand
Idle torque
80% >
SOC
>40%
TQreq
<40 Nm
All torque
demand
Idle torque
TQreq
>40 Nm
Torque assist
with 20 Nm
Torque above
40 Nm
SOC
< 40%
TQreq
<40 Nm
No torque All torque
demand
TQreq
>40 Nm
No torque All torque
demand

5. IX. Throttle Valve Control
The basis for throttle control is the feedback loop.
The input is the desired behaviour of mass flow
rate measured and it is compared with the actual
behaviour of desired mass flow rate to determine
the error signal of throttle angle correction. The
error signal is fed into control element that move
throttle plate at the valve. The actual value of the
throttle angle from the model is transmitted via
the feedback loop to the summation loop [1].
Here Programmable Integral derivative (PID)
controller is used to calculate the differential
error for feedback. There are two maps though
which controller decides the throttle valve angle.
Map 1 shown in figure 4 gives the throttle
preposition in comparison with Engine speed and
Mass flow rate of air measured at intake
manifold.
Figure 4 Map 1
Whereas the Map 2 shown in figure 5 gives the
required mass flow rate of air (Q_fair_required)
to achieve the desired torque output at given
engine speed.
Figure 5 Map 2
This required Qfair is then subtracted from the
Qfair measured to get the error mass flow rate of
air and fed to PID for real time feedback to
correct the throttle angle (Figure 7) . Engine
mode is also checked to avoid the actuation of
throttle plate in engine brake and idle mode.
There is another standard model for calculation of
idle speed mass flow rate, which adds the idle
speed throttle angle to corrected throttle angle
when engine is in idle mode.
Figure 7 Throttle valve control

6. X. Engine Mode Selection Strategy
Control
In this part, 5 modes can be defined the strategy
definition section [3]
1: Starting mode – Engine is started from rest
with help of starter motor. Position of key is first
checked. When key is giving cranking command
ECU gives signal to starter motor to provide
cranking torque of 12 Nm which is sufficient to
crank engine up to 1200 rpm for a few
milliseconds. After cranking as speed goes above
800 rpm engine gets off from starting mode.
2: Idle speed control
Engine idle speed assumed in this model is 800
rpm. When there is no load applied to engine it
must run at constant low fuel consumption mode.
But as soon as load is applied it must provide the
requested torque without stalling. Mass flow rate
of air is calculated though standard AMESim idle
valve control model which is not discussed in this
paper and this command is added to throttle valve
in throttle valve control model.
3: Engine brake mode
When brake pedal is pressed and/or engine is
running at zero loads while decelerating, engine
goes in this mode. This mode gives effective
reduction of speed while consuming the kinetic
energy in form of inertia gained by engine
flywheel.
4: Cruising mode
When engine is running below its red rpm i.e.
maximum speed then this mode is selected. This
mode provides moderate torque output which can
overcome wide range of load requests but below
high load requests.
5: Maximum speed mode
There is instance when driver presses the
accelerator pedal to its full depression; the load
on engine goes to its maximum value. To
overcome this load request engine should provide
maximum torque therefore this mode is activated.
Logical circuit diagram is for engine mode
control in figure 8; here four real time variable
inputs are compared for mode selections which
are Pedal position, Engine speed, Calculated Idle
speed and key position. Following equation gives
the mode after comparing mainly the engine
speed [3].
f(mode) = (x==0)*(y<=(z + DeltaIdleSpeed))*2
+(x==0)*(y> (z + DeltaIdleSpeed))*3
+ (x!=0)*(y<= (MaxSpeed - DeltaMaxSpeed))*4
+ (x!=0)*(y> (MaxSpeed - DeltaMaxSpeed))*5
Where, x = Pedal position
y = Measured Engine speed
z = Calculated idle speed
DeltaIdleSpeed = Range up to which idle speed is
allowed fluctuate
MaxSpeed = Maximum speed at highest torque
output
DeltaMaxSpeed = Range of cruising mode
A Command terminal is taken towards clutch
from pedal position logic because engine is not
connected to powertrain up to 30% depression of
accelerator pedal. Logic is applied to starter
motor on comparing measured engine speed with
stalling speed of engine. During this engine
starting mode is selected unconditionally.

7. XI. Simulation Parameters and Results
For validation of fuel consumption and
Simulation Honda Insight LX is chosen as
benchmark. The key reason behind selection of
this car is the similar architecture of powertrain.
Specifications shown in table 2 are used as
parameters in simulation and they are taken from
official website of Honda Insight [2].
For simulation NEDC and EPA highway driving
cycle are used. From NEDC the behaviour of
Engine and motor rotary speeds can be studied.
When torque requirement is less, only motor is
providing torque i.e. rotary speed is more and
engine is in idle mode. Whereas torque demand
increase is sensed by ECU and engine starts
running at higher speed to fulfil requested torque.
Simulation results of NEDC are shown in figure
8 and results of EPA highway are in figure 9.
XII. Calculation of mileage
In order to validate the model performance
mileage as comparing parameter is calculated.
Honda Insight LX has mileage of 44 on EPA
highway driving cycle according to data sheet
provided on official website [2].
Fuel consumed – 2078.62 gal/hr
Total Fuel consumed in 330 seconds – 190 gal
Linear displacement of vehicle in 330 seconds –
3.8761 miles
𝑀𝑖𝑙𝑒𝑎𝑔𝑒 =
𝐹𝑢𝑒𝑙 𝑐𝑜𝑛𝑠𝑢𝑚𝑒𝑑 𝑖𝑛 𝑔𝑎𝑙𝑙𝑜𝑛𝑠
𝐷𝑖𝑠𝑡𝑎𝑛𝑐𝑒 𝑐𝑜𝑣𝑒𝑟𝑒𝑑 𝑖𝑛 𝑚𝑖𝑙𝑒𝑠
𝑀𝑖𝑙𝑒𝑎𝑔𝑒 =
190
3.8761
Mileage = 49 gal/mile
Figure 8 Engine Mode selection strategy logic model

8. Table 2 Honda Insight LX Specifications
Parameter Specifications
Gasoline ICE Inline 4 cylinders
Displacement (cc) 1339
Horsepower @ rpm 98 @ 5800
Torque (lb-ft @ rpm) 123 @ 1000-1700
Redline (rpm) 6200
Bore and Stroke (mm) 73 x 80
Compression Ratio 10.8 : 1
Electric Motor - DC Brushless Motor
Power (hp @ rpm) 13 @ 1500
Torque (lb-ft @ rpm) 58 @ 1000
Electric power storage - (Ni-MH) Battery
Output (Volts) 100.8
Rated Capacity 5.75 Ah
Exterior Measurements
All-Season Tires 185 / 60 R15 84T
Wheelbase (in) 100.4
Length (in) 172.3
Height (in) 56.2
Width (in) 66.7
Track (in, front/rear) 58.3 / 58.0
Curb Weight (lbs) 2767
Weight Distribution 58 / 42
EPA Mileage Ratings / Fuel
City/Highway/Combined 41 / 44 / 42
XIII. Conclusion
Honda insight has mileage of 44 and model
discussed in this projected yielded mileage of 49
on EPA highway driving cycle. This validates the
efficient working of model.
Overall fuel consumption is reduced by use of
hybrid system.
Engine is running at idle speed for relatively
more time in comparison with similar
conventional gasoline vehicle. Hence emissions
are reduced.
Motor is providing initial torque demand for
acceleration hence smooth rise in speed is
observed. Acceleration of car is quite high which
is advantageous.
Battery SOC is being monitored continuously
hence longer battery life might possible.
XIV. Future Scope
Concept of regenerative braking is not applied in
this model, in future control logic for the
effective use of regenerative braking for smooth
deceleration and charging the battery will be key
work.
Simulating the emissions for reducing the NOx
generated at high temperature and HC emissions
generated at starting mode of engine.
Drivability comfort evaluation and optimization
using vehicle dynamics concepts. Sudden takeoff
from motor driven to engine driven gives a
impulsive vibration in powertrain which needs to
reduced by finding the perfect matching speed
though batch run of simulation at various test
rpm.

9. Figure 8 NEDC driving cycle simulations
Figure 9 EPA Highway Driving Cycle Simulation