The document describes modeling and control of an electric vehicle using MATLAB. It discusses modeling the battery state of charge, depth of discharge, and terminal voltage. Figures show the battery voltage and SOC during charging and discharging. It also examines electric vehicle gearbox systems, noting how multi-gear systems can increase torque and efficiency. The MATLAB model and figures presented analyze properties like battery capacity and internal resistance at different states of charge and currents.

1. MODELLING AND CONTROL OF E-
VEHICLE BY USING MATLAB

2. MODELLING AND CONTROL OF E-VEHICLE BY USING MATLAB
SubmittedBy:
VISHAL &
CHINMAY MISHRA
IN PARTIAL FULFILLMENT FOR THE AWARD OF THE DEGREE OF
BACHELORS OF ENGINEERING
IN
ELECTRICAL ENGINEERING
CHANDIGARH UNIVERSITY
AUGUST ,2022

3. BONAFIDE CERTIFICATE
CERTIFIED THAT THIS PROJECT REPORT “MODELLING AND CONTROL OF
ELECTRIC VEHICLE” IS THE BONAFIDE WORK OF “VISHALAND CHINMAY
MISHRA” WHO CARRIED OUT THE PROJECT WORK UNDER MY/OUR SUPERVISION.
HEAD OF THE DEPARTMENT SUPERVISOR
Dr. Ashutosh Tripathi, Dr Amandeep Gill,
Electrical Engineering Electrical Engineering
FOR THE PROJECT VIVA-VOCE EXAMINATION HELD ON
INTERNAL EXAMINER
Dr. Himani Goyal Sharma

4. PHASE 3:
DESIGN FLOW/PROCESS

5. ELECTRIC VEHICLE BATTERY- STATE OF CHARGE AND
DEPTH OF DISCHARGE:
• The development of energy storage technologies is essential to the electrification of
vehicles. The development of analytical modelling and real-time methodologies for
assessing battery condition is a crucial component of battery technology advancement.
By reducing over-discharge and over-charge, battery performance prediction techniques
will lengthen the battery's lifespan. Decent models, in the eyes of the designer, make it
feasible to do things like range prediction, which would not be possible without a good
model. In a more fundamental sense, battery models are essential parts of embedded
systems that ensure safe operation whether charging or discharging. They are also crucial
facilitators in "pushing the envelope," enabling optimal consumption, quick charging,
and other advanced features. To estimate the battery parameters, a reliable, user-friendly
battery model should be built.

6. CONT.
• A significant objective for the economic and social growth of many nations, as
well as the direction that cars will take in the future, is the creation of new energy
vehicles that are inexpensive, ecologically friendly, and green. Electric vehicles
(EVs), which have no emissions of any kind, may be compared to one another in
terms of their fuel efficiency. The battery technology governs how well and how
quickly electric vehicles evolve since it serves as their engine. Lithium-ion
battery design and performance improvement has therefore emerged as a key
area of study. These battery models are often tested by pulse charge/discharge
tests, and the model's accuracy in predicting the terminal voltage of the battery
from a particular current "input" serves as the assessment criterion.

7. CONT.
• The measurement is matched to the model's components in a MATLAB Simulink
simulation, which enables us to derive fundamental values like state of charge (SOC),
state of health (SOH), depth of discharge (DOD), and terminal voltage simulated under
a predetermined uncertainty value. This report opens the door for further research into
the application of a BMS to effectively manage each battery string.
• The use of MATLAB-Simulink to simulate the charging and discharging behaviour of a
battery made it possible to analyse the dynamic properties of a lithium-ion battery. The
lithium-ion battery cell's capacity, open-circuit voltage (OCV), and internal resistance
were studied at various states of charge (SOCs) and load currents.

8. MATLAB MODEL:

9. CONT.
• Since determining a battery's SOC is a difficult operation that depends on the
battery type and the application in which it is used, there has been a lot of
development and research done recently to increase the accuracy of SOC estimates.
One of the key functions of battery management systems is accurate SOC estimate,
which can assist increase system performance and dependability as well as the
battery's lifespan. It is difficult to precisely predict the SOC under diverse operating
circumstances, though, because battery discharge and charge involve intricate
chemical and physical processes.

10. MATLAB FIGURE:
Fig 1.2

11. MATLAB FIGURE:
Fig 1.3

12. MATLAB FIGURE:
Fig 1.4

13. OBSERVATION FROM FIGURES:
• It is clear from the above results that the key component of a battery management
system (BMS) for Li-ion batteries is the state-of-charge (SOC). Like the fuel gauge
in combustion cars, the SOC of electric vehicles shows how much charge is still in
the battery. A proper understanding of SOC plays a significant role in the battery's
durability, performance, and dependability. Since the electrical energy stored in the
battery powers propulsion systems at a cheaper cost than fossil fuel, more battery
energy consumption signifies a deeper depth of discharge (DOD) and lowers energy
consumption cost (ECC).

14. CONT.
• It should be noted that the ideal DOD cannot be determined by the DP using
the battery ageing model since it needs the upper and lower SOCs to be
established in advance. When the battery life model is considered, the PMP
with a free lower boundary value outperforms the DP in terms of determining
the ideal DOD. A greater DOD, however, also denotes more battery discharge,
which accelerates cell ageing and raises the cost of equal battery life loss
(EBLLC).

15. ELECTRIC VEHICLE GEAR BOX SYSTEM:
• To enhance the sound quality, the gearbox's construction has been changed using optimization
techniques. The use of a high-speed, low-torque machine is made. Along with speed, the gearbox
also transforms torque and power at the vehicle shaft. The model has both driving and recovery
modes. The ability of the transmission system to change gear ratios without engaging or
disengaging individual gears is an intriguing feature. As a result, gear changes may be made
smoothly regardless of the load. The fundamental structure of the power management (PM)
system in electric vehicles (EVs) consists of two layers: high level software-based supervision
and low-level hardware-based control, which may be further subdivided into low level
component and low-level control. The PM system in EVs is optimised by combining the efforts
of the hardware and software control layers.

16. CONT.
• Each wheel in a BEV has its own fixed gearing and electric motor to
improve the cornering capability. The BMW i8 Supercar is the only plug-in
vehicle currently in production that has a two-speed gearbox. It makes use of
the gearbox to achieve high wheel torque at both low and high speeds.
Additionally, multi-gear systems have been thought of to minimise machine
size and increase system effectiveness. To obtain the needed wheel torque
and maximal vehicle speed, modified versions of the current IPM machine
are coupled with gearing in the single-speed gearbox systems, which are
intended as alternatives to the existing prototype two-speed system.

17. MATLAB MODEL:

18. MATLAB FIGURE: