More Related Content Similar to MidtermReport (20) 2.
Table of Contents
I. Introduction…………………………………………………………………………………….. 2
A. Background……………………………………………………………………………. 2
B. Motivation.…………………………………………………………………………….. 2
C. Project Definition…………………………………………………………………….... 3
D. Objectives…………………………………………………………………………….... 3
II. Project Task Description……………………………………………………………………….. 4
III. Experiment and Theoretical Methods………………………………………………………….. 4
A. Unknown Slope………………………………………………………………….….…. 4
B. Rolling Coefficient…………………………………………………………………….. 5
C. Drag Coefficient……………………………………………………………………….. 6
IV. Work Schedule and Progress to Date…………………………………………...……….……… 6
A. Work Schedule……………………………………………………………...….……… 6
i. Weeks 12……………………………………………………………………... 7
ii. Weeks 34……………………………………………………………….…….. 7
iii. Weeks 58……………………………………………………………...……… 7
iv. Week 9………………………………………………………………………… 7
v. Week 10……………………………………………………………………….. 7
B. Progress to Date on Tasks……………………………………………………………… 8
V. Team Assignments and Organization…………………………………………………………... 8
A. Nicole Aguirre…………………………………………………………………………. 8
B. Justin Bosch…………………………………………………………………….……… 8
C. Sik Cho……………………………………………………………………………….... 8
D. Gene Lee………………………………………………………………………………. 9
E. Yu Zhang………………………………………………………………………………. 9
VI. References…………………………………………………………………………………….... 10
VII. Appendices……………………………………………………………………………………... 11
1
3.
I. Introduction
A. Background
The development of the world is accelerating at an incredible rate with new and advanced
technology being developed on a day to day basis and more people having access to basic technology all
over the world. Sustainable technologies, in particular, have been challenging prevailing business
practices, especially within industries that depend heavily on the use of fossil fuels. And with the world’s
need for mobility booming, less polluting vehicle technologies must be developed if this industry does not
want to continue pumping greenhouse gases and pollution into the atmosphere. One solution is the
introduction of electric propulsion to power these vehicles. Electric vehicles significantly reduce air
pollution, greenhouse gases, and the use of petroleum. And with modern day technology improving the
way we use batteries, these electric vehicles are pivotal for the world’s future.
B. Motivation
Electric vehicles utilize a simple motor that often achieves 90% energy conversion efficiency and
can be precisely controlled. Unlike a traditional fuel powered car’s battery, which serves the purpose of
starting, lighting, and ignition, an electric vehicle’s battery is designed to give power to the entire car over
a sustainable period of time. To achieve this, a typical electric vehicle may utilize a large battery pack that
consists of many discrete cells connected in series and parallel to achieve the total voltage and current
requirements of the pack. These large stacks of cells is typically grouped into smaller stacks called
modules, which are typically placed into a single pack that are welded together. With this design,
however, drivers must charge their car’s battery every time the power runs low. And with the latest
battery charging technologies, drivers would need to wait a minimum of 30 60 minutes for their cars to
recharge to maximum capacity, and typically even longer when charging from their homes. This
prolonged charging mechanism and inconsistency have caused many drivers to avoid purchasing electric
vehicles.
2
4.
C. Project Definition
In order to solve this problem of having to wait to charge your car and not knowing when and
where a driver will be able to find a recharging station, the MBEAM project had begun. First developed
and founded at the University of California, San Diego, the MBEAM project utilizes the same modular
batteries, but rather than welding them together into one single pack, each module of batteries is capable
of being taken in and out of the vehicle. What this allows is for drivers to be able to swap out their
depleted batteries and simply replace them with fully charged batteries. This can help to alleviate range
anxiety that drivers may have and also drastically reduces the time it takes to ‘recharge’ a vehicle.
Currently, the electric vehicle is a converted Volkswagen Golf that once ran on gasoline. In the vehicle, a
controller and an electric motor have been installed as well as different data acquisition programs that
measuring voltage and current.
D. Objectives
The objectives are to demonstrate the feasibility of a swappable modular battery solution by
analyzing and understanding the efficiency of these batteries and how to maximize the
electricaltomechanical power conversion. In order to do so, a set of test plans will be created to lay out
specific steps in how certain unknown values will be calculated as well as performing test drives to gather
data on voltage and current and mechanical outputs such as velocity, acceleration, and torque. Improved
models of energy consumption will be applied to create a road map with battery exchange pit stops for a
cross country drive.
II. Project Task Description
Based on the theories covered earlier, 5 major tasks for the project emerged, all accomplished by
performing test drives and analyzing the data collected. First of all, students need to verify slope
calculations, and determine the relationship between steepness of the road and the power consumption.
3
5.
Students will use GIS/GPS data to track of uphill/downhill movement of the car, and measure the voltage
and current during the drive. Acceleration in 3 directions are also measured, and these can be used to
verify the slope of the hill. Then, the next task is to determine the rolling coefficient of the road. This is
the constant variable in the first term of equation. This will allow students to understand howCr Pm
much energy is used to keep the car rolling forward. Another task that students need to resolve is to
design a fixture for pitot tube, and determine an optimal location to place the pitot tube in order to
measure wind velocity in streamline. After designing and building the fixture for pitot tube, the team will
test placing the device on hood of the car, roof of the car, and tail of the car. With pitot tube at optimal
location, students will analyze the effect of wind on energy consumption, and understand the effect of
drafting behind a freight truck. Lastly, using GIS data and experimental results, students will create a road
map with pit stops for battery exchange. The range algorithm will be further tested through a
mediumdistance drive from San Diego to Irvine/Long Beach. Perform the drive to verify predication and
plans. The specifics and approach for each task will be covered in detail in the experimental plans.
III. Experiment and Theoretical Methods
A. Unknown Slope
The objective of our first experiment and set of test drives is to correlate the acceleration data
retrieved from the MyRio inside the car and the slope of the road the car is driving on. The tests will be
run on two different road conditions (flat road and a known, relatively constant slope) with two different
acceleration conditions (no acceleration and constant acceleration). In order to find roads with these slope
conditions, we will use data of the topography of San Diego available from the SanGIS Data Warehouse.
The first part of the experiment is to drive on a flat road with no acceleration. We will be running
the flat road tests in a large parking lot in the early morning because the change in elevation is very slight
and traffic will be minimal at this time. First, we must maintain a constant velocity while driving so that
4
6.
the car has no acceleration. Then, we will collect data from the MyRio accelerometer. Ideally, the
acceleration in the direction of drive with respect to vertical acceleration should be zero. If this is not the
case, we must determine a relationship constant between the slope and the acceleration ratio ( ). Next,z′′
x′′
we will drive again on a flat road but with constant acceleration. We will run a number of test drives with
different values of acceleration. Ideally, the difference between the accelerometer reading in the direction
of the drive and the calculated acceleration of the car should be zero, which would make the acceleration
ratio also zero ( = 0). The acceleration of the car is simply the change in velocity over time ( ).z′′
x −V′′ ′c
Δt
V −V′ ′0
Then, the slope of the road can be determined by either equation: = or = ,α ( )tan−1
z′′
x −V′′ ′c
α ( )sin−1
g
V −x′c ′′
which should theoretically be zero during the duration of this test.
The next part of the experiment is to drive on a sloped road with no acceleration. To find an
acceptable area, we will create an elevation profile of the Interstate5 in the Carlsbad to Oceanside area
and consult Lou for a feasible stretch of road. The no acceleration portion of the test drives is the same as
the drives on the flat road. However, the acceleration ratio should reflect the slope determined with the
GIS elevation profile ( ). Next, we will drive the sloped road but with constant acceleration.( )tan−1
z′′
x′′ = α
We can again study the relationship between the accelerometer readings and the calculated acceleration
which should ultimately give us values which reflect the GIS elevation profile.α
B. Rolling Coefficient
For this test, we will again need to drive on a flat road, similar to the road in first half of the
Unknown Slope test. We will drive the car at a constant and slow velocity (5 mph or less) so that we may
neglect acceleration and drag forces. Also, we must assume perfect conversion of electrical to mechanical
power to find the rolling coefficient; at 100% efficiency, electrical power output is equal to mechanical
power output. Using the rolling force equation with the efficiency assumption ( ), wemgVPm = Pe = cr c
can solve for the rolling coefficient.
C. Drag Coefficient
5
7.
First, we must find a way to securely and durably attach the pitot tube to the suction cup base
provided by Lou so that the pitot tube can collect air speed data during the duration of all test drives and
so that it can be moved around the car as needed.
Then, we need to find a location on the car where the pitot tube experiences the most laminar
flow with little turbulence due to the car’s shape or other wind interferences (for example, the bottom of
the car is extremely turbulent due to the wind's interaction with the road itself), To do this, we will attach
the tube at various locations on the car (i.e. top of the roof, top of the hood, passenger door) and drive at a
few test velocities and collect voltage readings. We then need to plot this data and see which location
provides the least measurement noise during the drive.
Then, to determine the drag coefficient, we need to run test drives during a nonwindy day, so
that we can make the assumption that car velocity and wind velocity are equal. We will do multiple test
drives at varying velocities (20, 30, 40, 50 mph, etc.). The voltage measurement and wind velocity are
expected to have a quadratic relationship. We can then find the drag coefficients for the quadratic fit so
that for any given voltage reading from the pitot tube, we can easily return the wind velocity.
IV. Work Schedule and Progress to Date
A. Work Schedule
The following subsections outline a week by week breakdown of the project tasks and goals.
i. Weeks 12
The first two weeks of the project consisted of getting into contact with the project advisor, Professor De
Callafon, and discussing the goals and visions of the MBEAM project. Theoretical analysis was done to
develop a thorough understanding of the factors that affect the power required to move an electric vehicle
(EV). A Gantt chart was also created to help organize, pace, and distribute tasks for each team member
ii. Weeks 34
6
8.
The next couple of weeks were dedicated to writing and finalizing the experimental test plans and project
tests to see how much each factor of the power equation affects the efficiency of the EV.
iii. Weeks 58
These middle weeks are to acquaint the team with the EV and do the bulk of the data collection. The
procedures written in weeks 34 will be carried out in testing the effects of slope, rolling resistance, and
drag forces on the EV. To get a better measurement for the drag effect on the car, a suction cup pitot tube
assembly will also be designed to relocate the pitot tube from underneath the front bumper to the tail end
of the roof for a more precise wind pressure measurement during the drag coefficient tests. Throughout
these four weeks, we will use MATLAB to graph and analyze the raw data from the test drive for each
experiment.
iv. Week 9
After completion of all the data collection and analysis, rough estimates of how different factors impact
the efficiency of the EV will be used to to map out the battery exchanging pit stops for the crosscountry
drive.
v. Week 10
The last week of the project will be to organize and finalize all the data and analyses to prepare for the
project presentation in front of the advisors, professors, and students.
B. Progress to Date on Tasks
As of May 2nd, 2016 (the beginning of week 6), contact with advisors, theoretical analysis, and
the Gantt chart have been completed. The test drives and data collections have just begun to acquaint the
team with the MBEAM EV hardware and software. Experimental test plans written in weeks 34 have
been revised but may have an ongoing process of modification as procedures may not run as smoothly as
anticipated (traffic, wind, electromagnetic interference, etc.). The next steps include fabrication of the
pitot tube assembly, execution of the written experiment procedures, and analysis of the data. After these
7
9.
steps, the crosscountry pit stops will be roughly estimated based on the analyses and GIS data, and the
project will be presented.
V. Team Assignments and Organization
All team members assist on all tasks, but certain members specialize in certain areas.
A. Nicole Aguirre
Nicole has prior experience using GIS and employs ArcMap to find routes for test driving. Using a
combination of topography information from SanGIS, Google Maps, and a MATLAB script that returns
elevation profiles, she finds areas in which to test drive the EV based on distance, slope, and other factors.
This same process will be used to plan out a 200 mile test route and potentially a cross country road trip.
B. Justin Bosch
Justin is responsible for the creation and upkeep of the Gantt chart, ensuring the team’s progress remains
on track. Should any delays in the test plan occur, Justin updates the Gantt chart to reflect realistic goals
and deadlines. He also is gaining experience in operating the EV and collecting the raw data during test
drives.
C. Justin Cho
Justin takes the lead on all team communications. Internally, he tracks the team’s progress and ensures all
deadlines are met and all meetings with project and team advisors are adequately prepared for. Externally,
Justin creates all of our presentations and is looking into compiling the team’s work into a website for
future reference.
D. Gene Lee
Gene utilizes his strong understanding of physics and mechanics to aid the team in fully understanding
and further implementing the basic concepts behind an EV. The derivation of the equations involved in
converting electrical power into mechanical power will be used during future efficiency tests to determine
the best ways to handle the EV.
8
