RBS Regenerative Braking System

(for Bicycles)

ME 599-2003-02

by: Michael Resciniti

Adi Peshkess Peter Leonard

Date:

12/15/2003

Abstract When riding a bicycle, a great amount of kinetic energy is lost when braking, making start up fairly strenuous. The goal of our project was to develop a product that stores the energy which is normally lost during braking, and reuses it to help propel the rider when starting. This was accomplished with a spring and cone system whose parameters were optimized based on engineering, consumer preference, and manufacturing models. The resulting product is one which is practical and potentially very profitable in the market place. A spring (of tension 22,100 N/m) is stretched (at most 37cm) by a wire which wraps around a cone (of 15 cm large diameter and 2 cm small diameter), while braking. A clutch is then released and the cone drives the bike’s gears to assist the rider while starting. The product weighs 14 lbs, will cost $87, and will return 85% of the rider’s stopping energy when starting up again.

Nomenclature D = stopping distance - parameter wr = weight of rider - parameter wb = weight of bicycle (plus weight of product) - parameter g = gravitational constant - parameter µ = coefficient of friction between bicycle tire and asphalt - parameter α = acceleration of bicycle during stopping - parameter N = normal force on bicycle tire due to gravitation - parameter vi = initial velocity of bicycle - parameter vf = final velocity of bicycle - parameter rt = radius of bicycle tire - parameter Ff = force of friction on bicycle tire - parameter θw = angle of wheel traversed during stopping - parameter τ = torque on bicycle tire applied by product - variable rg1 = radius of large gear - variable rg2 = radius of small gear - variable rc1 = large radius of “cone” - variable rc2 = small radius of “cone” - variable Lc = length of “cone” - variable θa = angle of “cone” rotation at applied point - variable θt = total angle of “cone” rotation for complete winding - variable x = deflection of spring - objective (min) L1 = initial length of spring - variable L2 = final length of spring - variable rs = average radius of spring coil - variable tw = thickness of spring wire - variable ks = spring constant - variable Πs = material of spring - variable ms = mass of spring - variable Cs = cost of spring* - objective (min) mp = mass of product* - objective (min) C = cost to manufacture product* - objective (min) S = selling price of product* - objective (max) P = profit from sale of product* - objective (max) * for later optimization of cost and weight. For the purposes of this proposal, we are only attempting to minimize the necessary length of the spring deflection (x)

1.1 The Product Design Problem Bicycles have been the heart of human transportation since the dawn of its creation. Many advances have been made to make the bike more desirable and friendly for the millions of users throughout the world. In many countries throughout Western Europe, a very large number of professionals use bicycles to commute to work in their business suits with their briefcases. It is our goal to design a device that can make their commute an easily traveled one. The Regenerative Braking System (RBS) is a device that can do so by reducing the overall energy the day to day business commuter is required to use.

1.2 Product Development Process Many decisions need to be made in order to produce the most desirable and affordable product to make the highest profit and most unique device. The flow chart in figure 1 shows how our product fits into the product development process. There are three distinct phases: the Concept Phase, the Design Phase, and the Production Phase. During the Concept Phase, we defined the problem of losing energy while braking on a bicycle. We then conceptualized different ways of using that energy with different regenerative braking systems. Through research and customer surveys, we entered the Design Phase knowing consumer preferences. We generated designs based on known preferences, constraints, and parameters. We then made a CAD drawing of our design. We analyzed our model from the viewpoint of the consumer and manufacturer and did a profit analysis of the optimal designs. After reviewing our results, we hypothesized how we would enter the Production Phase. Because this product would be produced in bulk, we took into account the price of machinery, storage, labor, etc. After all of these costs were accounted for, we analyzed potential profit again to make sure we would still make money. Initial results indicate that we would eventually make a profit if this product were actually placed in the market. (Insert flow chart)

1.3 Design Requirements There are many requirements that need to be met to produce a product that is both feasible and optimal. There are also some constraints, both geometric and engineering that also need to be satisfied. The following list describes these requirements and constraints: 1. Store energy while braking This is the main requirement and the overall objective of the device and must be

suitable to meet the customer’s needs.

2. Return energy to start up Once the energy is stored in the device, it is necessary to have a simple way to

release this energy back to the user in a positive way. This can be accomplished with an innovative gear system.

3. Must fit on a bicycle This is one of the most difficult constraints to achieve and most important because

we are dealing with such confined spacing. The objective is to fit the length of the spring on the longest part of the bicycle, which is slightly less than a meter.

4. Light weight The importance of having a light weight design is driven by the customer’s desire

to have a bicycle that is more maneuverable and more portable. This is also a direct trade off with how much energy can be stored in the spring.

5. Good stopping range The stopping range is important because this product needs to be usable in real

life situations. This component can be optimized to have the shortest stopping distance using dynamic analysis.

6. Good stopping force The force required to stop is dependent on the stopping range and the comfort

levels of the rider. It is also related to the possible spring features. 7. Inexpensive and affordable This product must be able to make a profit and be desirable. The driving force for

the price can be directly related to the spring size as shown later in the paper. 8. Safe to user and environmentally friendly Safety is always a very important aspect when ever there is a consumer product.

This requirement will be addressed after the initial design is created. 9. Profitable Profit is usually the main motivation for the start of any company, therefore this is

one of the parameters that will be optimized. 10. Reliable It is important to have a product that is reliable and this requirement will affect

the long term business image and needs to be maintained in high regards. 11. Manufacturability In order to make anything profitable, it needs to be manufacturability, hence the

important of having a product that can be made easily and cheaply. 12. Aesthetically pleasing

This is not a requirement that needs to be taken heavily, but the design should always have nice look about it, because looks will persuade the buyer.

13. Modular Having a device that can be adapted to existing bicycles is essential to sell the

greatest number of units. This also can reduce other types of manufacturing costs. 14. Should not hinder normal riding To have a successful accessory for a bicycle, the ride should not feel a noticeable

change in the biking performance or in the normal riding motion. A device that impedes the normal biking experience would be considered undesirable.

15. Controlled release The energy that is released back to the user must be done in a safe and

manageable fashion. This can be a consideration after the prototype is completed. The main requirements that are used in the analytical model were reduced to price, weight and capacity (percent of the energy returned). All of the previous design requirements were used in the engineering model to describe the reduced requirements. Some of our design decisions are quantifiable, while others are not. The ones that are and their associated equations are as follows:

2. Engineering Design Model

2.1 Design Requirements in terms of Design Variables The following describes the requirements that were met in section 1.3 and relates them in terms with the design variables, so they can be calculated inside of the optimization model. 1. Store energy while braking ½mv2 = ½ kx2

2. Return energy to start up ½ kx2 = ½ mv2

3. Must fit on a bicycle Ld < Lb, Rd < Amax4. Light weight min(mass) 5. Good stopping range D = [10 ft., 100 ft.] 6. Good stopping force Ff = µN 7. Inexpensive and affordable min(cost) 8. Profitable min(cost) From this list, #1, 2, 3, 5, 6 are quantifiable using engineering analysis. They can be analyzed with equations from physics, dynamics, kinematics, and geometry. Requirements #4, 7, 8 must be done through mathematical iteration and cost analysis.

2.2 Objective and Constraint Functions The complete design optimization model in negative null form is as follows: Objective: min x

Subject to: ½·m·vi2 – τ·D/rw – Ff ·D = 0

Ff – α·m = 0 Ff – µ·N = 0 N – m·g = 0

m – (wb + wr)/g = 0 τ·D/rw – ½·ks·x2 = 0

θw – D/rw = 0 rg1·θt – rg2·θw = 0

Lc – SQRT[(tw·θt/2π)2 – (r1-r2)2] = 0 x – r1·θa – (r2 – r1) ·θa

2/2θt = 0 xmax – ½·θt· (r1 + r2) = 0

xmax < 3 ft.

D < 100 ft, D > 10 ft. vi = 5 mph. wb = 30 lbf.

wr = 180 lbf. µ = 0.7

rw = 13 in. Figure 1

x

rc2

rg1rc1

Lc

rg2

Attached to tire

2.3 Optimization Model and Solutions Two steps were done in order to complete the design optimization model. The first thing that needed to be done is to find what the optimal stopping distance must be before we can determine what the shortest spring length should be. This device is only using the rear brake to slow the bike to a stop. As the bike begins to slow, the weight is transferred to the front tire, therefore the normal force on the rear tire is reduced, producing less stopping force than. The excel model in figure 2 shows the maximum stopping force and therefore the minimal stopping distance. This force is then extracted from the model and inputted into the optimization model for the minimal spring length. Now knowing the maximum stopping force, we can calculate the stopping torque and use the solver to find the minimal spring length as shown in figure 3.

Figure2: Optimize to find the Minimal Stopping Distance

Finds the Minimal Allowable Stopping Distance (in Meters) Variables and Constants Constraint Equations vi 5 m/s Rf + Rr - W = 0 0Rf 420.428571 N -Rf(L1) + Rr(L - L1) + f(h) = 0 1E-06Rr 462.471429 N W 882.9 N L 1.5 m Note: Only uses back brake to stop L1 1.1 m f 231.2357145 N u 0.5 h 1.2 m D 4.865165411 m Output Parameteres rw 0.33 m T 76.30778579 Nm θ 14.74292549 rad Energy 1126.147959 J INFO m 90 kg a 2.569285717 m/s2 t 1.946066164 s g force 0.261904762 g

Figure 3: Minimize to find the Shortest Feasible Spring Length Min feasible spring length

Input Parameters Constraint Equationsrw 0.33 m T-k*xi*ri = 0 (equation in matlab)T 86.75221471 Nm E - .5 * k * (xf-xi)^2 = 0 (equation in xf)θ 12.96796864 rad Theta - ((xf-xi) / rave) = 0 #NAME?Energy 1126.147959 JPercent E return 100%

Variablesc (gear ratio) 1.136872389k 25000 N/mri #NAME? mrf #NAME? mrave #NAME? mxi 0.046908859 mxf 0.347061881 m

2.4 Interpretation of Results The solver found that the minimum spring compression length is 0.35 meters, and by using a common rule of total spring length is 1.5 times the compression length the total spring length is 0.52 meters or almost 21 inches. The spring constant was chosen to be in a reasonable range of 25000 N/M, but the spring length seems to converge around the same optimal length as k goes higher. The only active constraint that is present is the final radius of the cone. This active constraint is expected because the smaller the final radius is the less the spring will be compressed and with the number of times the wheels rotate.

3 Our Product in the marketplace.

3.1 Benchmarking

There are no other products exactly like the RBS currently in the marketplace. However, there are several products available to consumers which make bicycle transportation easier. One product is an electric bike which uses pedaling to store energy in the batteries of the bicycle, and then to re-use this energy from the batteries (via an electric motor) to assist when riding a bicycle uphill.1 Another vehicle which uses regenerative braking is a two-wheeled electric scooter which uses the braking system to recharge the batteries. However, this stores energy as electrical rather than mechanical

1 http://www.electricvehiclesnw.com/main/regen.htm

energy.2 However, we have come across no product currently on the market for a purely mechanical regenerative braking system (RBS)

3.2 Patent Search One patent of note was found during our patent search was Patent #4,744,577.

This is a patent for a mechanical RBS for a bicycle, using an elastic band as the energy storage device. This appears to be a device that is integrated with the bicycle, and not able to be added to any bicycle bought separate from the device. However, it does not appear to be currently marketed, as the patent was established in 1988 and no device of this sort has been seen since.

3.3 Maximizing Profit

In order to determine how well our product will perform in the market, we must reformulate our objective. Our new objective function will be the maximization of the profit returned from the sales of the RBS. Our costs will be determined by the materials and parts we use in the device. We can keep this low by minimizing/maximizing the following variables:

MAX(profit) = MAX(revenue – cost)

MIN(spring strength: k) MIN(spring length: x) MIN(cost per spring: Ck) MIN(cone length: L) MAX(difference of cone radii: rf-ri) MAX(angle of cone rotation: θ) MIN(# of parts purchased: N) MIN(cost of parts purchased: Co) MAX(selling price: P) MIN(start-up costs: Cs) MIN(tooling costs: Ct) MAX(# units sold per year: n) MIN(# workers: w) MIN(salaries: S(wi)) MAX(# years in service: Y) Revenue per year = R = P·n Start-Up-Costs = Cs = (Cost of Machines: Cm) + (Cost of Facilities: Cf)

2 http://www.electricstar.org/motorboard.html

Cost per product: Ck·F(k,x) + Ct·G(L,rf,ri,θ) + Co·N

Profit for one year: P·n – [Ck·F(k,x) + Ct·G(L,rf,ri,θ) + Co·N] ·n – Cs – ΣS(wi) We created an excel spreadsheet to optimize this new problem:

4 Model Extension: Marketing

4.1 Market size

he size of the market can not be found by looking up previous data, because the

s are l

be

is estimated that 1.5 billion people own and use a bicycle world wide and 100 – 120 e

4

SOLVED | NOMINALSpring length (x) m : 0.1 | 0.3

Spring strength (k) N/m : 5000 | 10000Cone Length (L) in. : 0.5 | 3

Cone Large Radius (ri) in. : 0.2 | 6Cone Small Radius (rf) in. : 0.1 | 0.1

Cone Rotation (θ) rad : 6 |Number of parts purchased (N) : 25 | 25

|Spring Cost (Ck) : $1.00 | $6.00Tooling Cost (Ct) : $0.03 | $4.58

Purchased-parts Cost (Co) : $12.50 | $12.50|

Start up Costs (Cs) : $500,000.00 | $500,000.00Salaries (S) : $1,000,000.00 | $1,000,000.00

|Selling Price (P) : $85.00 | $85.00

number sold : 100000 | 100000|

Revenue : $8,500,000.00 | $8,500,000.00Cost : $2,852,500.00 | $3,807,500.00

|Profit : $5,647,500.00 | $4,692,500.00

TRegenerative Braking System (RBS) is a new product and no data exists yet. The research found consists of: how many bikes are in the world today, how many bikepurchased in a year, and how many “electric assisted” bicycles are purchased in a year alin different countries. The “electric assisted” bicycles is the most similar to the RBS because they can both be added-on to a bicycle and they both serve similar purposes. The major difference between these products would be price, in which the RBS would much cheaper. Itmillion bicycles are produced every year. (data taken 11/3/2003) The break down of thcountries is as follows:

Standard Electric @Price

China 450

rom this information we can make some approximation of supply and demand. If the k

M 1 M $300 India 300 M - - USA 120 M 35,000 $1,500 Japan 70 M 20,000 $750 Brazil 40 M - - Europe 140 M 65,000 $1,000 FRBS is sold near 100$, then we can find the corresponding data. An example would loolike this:

China

0100000000200000000300000000400000000500000000

$0 $100 $200 $300 $400

herefore, the market in China would be $50 for the bike plus $100 for the RBS would

sing this approximant method we find that the market is:

hina: 250 M

f we approximate the rest by 50%, then the total market yields:

10 Million!

his is an extremely large number, so if it was only 1% of this, then profit margins can

4.2 Utility

he utility is derived from the characteristics that were prescribed: price, capacity, and weight. The surveys are used to find this utility in terms of the Beta values. The following are the Beta values:

Tyield a market near 250 million. U CUSA: 110 M Japan: 60 M Europe: 120 M I 7 Tstill be incredible.

T

Price: -0.0529 Capacity: 0.0512 Weight: -0.2164

that the consumer cares about the weight the most, then price and his is saying is that people want a product that will give back some

nergy that is really light and somewhat cheap.

.3 Logit Model

n orthogonal fashion in order to do a conjoint analysis. This acteristics at 3, 3, and 2 levels. These characteristics consisted

f price, capacity and weight. Price is obviously how much the unit will cost and the two e

r tween

e utility section. The spline interpolation as applied to find the continuous functions. As shown in figures 4, 5, and 6, these

These values showcapacity. What te

4 A survey was devised in asurvey had 3 product charolevels were $75 to $100. The reason it was only varied between two levels because pricis very predictable and does not need as much detail. Capacity is defined as the percent of energy returned to the user after braking is completed. This had three levels, 50%, 75% and nearly 100%. Another characteristic thought to have impact on whether or not a customer will buy the product is weight. Weight is how much the total system added to the bicycle. This had three levels, 5 lbs, 10 lbs and 15 lbs. Weight was thought to be very important because the trend of bicycles has been going toward lighter, but most importantly is the trade off between a light system and pricing and capacity. All of the factors have the greatest affect on the spring size, so the model can be reduced to focusing on their relationship to the spring. The survey also included some addition personal information. The rider’s sex, weight, normal riding speed, and riding reason foriding were asked. This information as used to determine trends or correlations begroups of people. It was also used to reconfirm some boundary conditions previouslycalculated. Interestingly enough, the persons’ average riding speed was 12.93 mph, which is almost exactly what was used in the engineering model. Also nearly 100% of the survey’s population used a bicycle for recreation or commuter purposes, which means that they would all be included in the market. The data was collected, the maximum likelihood formula was applied and the betas were calculated. The results were discussed under thwresults can be approximated as linear.

Beta vs w eight

y = -0.2164x + 3.2475

0.000

0.500

1.000

1.500

2.000

2.500

5 10 15

lbs

Weight

Linear (Weight)

Figure 4: Utility vs. Weight

Beta vs Price

y = -0.0529x + 2.7567-3.000

-2.500

-2.000

-1.500

-1.000

-0.500

0.00075 85 95 105

$

Price

Linear (Price)

Figure 5: Utility vs. Price

Beta vs Capacity

y = 0.0512x - 2.7563

-0.500

0.000

0.500

1.000

1.500

2.000

2.500

50 70 90 110

% Returned

Speed

Linear (Speed)

Figure 6: Utility vs. Capacity

5 ANALYTICAL TARGET CASCADING

We have so far discussed how to optimize the RBS from three points of view: engineering, manufacturing, and customer. The engineer attempted to minimize the amount of spring deflection (x) for a given value of spring stiffness constant (k) based on a minimum stopping distance (D), which was derived from a physical description of the system. The manufacturer considered the effect of k and x on three design characteristics: cost to manufacture, weight of the product, and the capacity of the product to return energy to the rider. The customers were presented with surveys and asked for their preferences of characteristics for the product based on the weight, capacity, and retail price of the product.

We were able to model our profit by multiplying 40% of the selling price P by the demand q, which was based on our demand model from Assignment 3. There is little deviation, however, between the profile of the demand model and that of the profit model, as can be seen in figures 7 and 8. The only major difference in the profiles is near the region of high k and low x, which lies in an undesirable range (price is too high while the capacity is too low).

We then compare the demand model to the manufacturing model, in figure 9.

We can then use iteration to find a balance point between these two models. Our targets at the top level are to keep the spring length and spring constant in a balance for

Figure 7: Demand Model Figure 8: Profit Model

Figure 9: Producer Model (next to Demand Model for comparison)

0.10.20.30.40.50.60.70.8

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Spring Deflection (x)

Demand Model550-600

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Spring Constant (k)

Producers Model 280-300

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80-100

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Demand Model550-600

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spring deflection (x)

spring constant (k)

Profit22500-2500020000-2250017500-2000015000-1750012500-1500010000-125007500-10000

our stopping distance from our engineering model. We then pass that target to the Producer model, and then the Demand model.

First, we start on the engineering curve and choose a point from the curve to start our iterations. We decide to use the point on the curve that yields the highest profit. From there we follow the gradient of the Producer Model, which leads us to the high point of the Producer model. Then we follow the gradient of the Demand model at that point until we hit a boundary. From this point on the Demand model, we follow the gradient of the Producer model until we hit a boundary again. This continues until our iteration moves between two points only. The following sequence is what occurs: Model Gradient start (x,k) finish (x,k) Producer (0.3, 30000) (0.1,30000) Demand (0.1, 30000) (0.35, 5000) Producer (0.35, 5000) (0,1, 5000) Demand (0,1, 5000) (0.8,15000) Producer (0.8,15000) (0.6, 5000) Demand (0.6,5000) (0.8, 25000) Producer (0,8, 25000) (0.55, 5000) Demand (0.55, 5000) (0.8, 25000)

So our two models find equilibrium along the line between the points (0.8 m, 25000 N/m) and (0.55 m, 5000 N/m), as shown by the yellow line in Figure 10. Now we can return to the engineering model (marked by the red line in Figure 10), which indicates the optimal curve fit of k to x for our best stopping distance of approximately 5 meters. These two lines meet when x is approximately 0.58 meters and k is 7500 N/m. These values yield a suggested selling price of $63.88, a capacity of 70% of speed returned, and a weight of 11.26 lb. While the capacity and weight are nicely within our pareto boundaries, the price (as will be shows in our business plan) will need to be raised significantly in order to make a profit.

Figure 10:Lines of Equilibrium. yellow: producer-demand red: engineering performance Overlay on Producer Model

0.10.20.30.40.50.60.70.8

5000

0000

15000

20000

25000

30000

1

Spring Deflection (x)

Spring Constant (k)

roducers ModeP l 280-300

260-280

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80-100

Comparing this solution with that found only by optimizing the profit in EXCEL, we see the following: EXCEL SOLVER for Profit Analytical Target Cascading spring deflection (x) 0.37 m 0.58 m spring stiffness (k) 30,000 N/m 7,500 N/m Price ($) $99.31 $63.88 Weight (lb.) 16.32 lb. 11.26 lb. Capacity (% of 1800J) 114% 70% Profit $32,086,000 $21,118,000

So, the excel solver seems to have created a more profitable outcome. However, the selling price was determined by increasing the manufacturing cost-per-part by 60%. Therefore, we can increase our profit by raising the selling price, and our demand curve indicates that our profit will actually increase almost 30% by an increase to a selling price of approximately $85 if we increase the capacity to approximately 85%. We can do this by setting x to 0.37m and k to 22,100 N/m, and this also yields a weight of only 14 lb. This appears to be the true optimum of our system.

6 Conclusion The overall goal was to design the Regenerative Braking System while keeping the engineering, producer and customer models in check. The key design decision was based on the spring length and the spring constant. The reason why this feature was used more than all of the other features are because the other features would not have as much effect on the complete system. By changing the size and spring constant, desirable price, weight and capacity can be realized. We used a survey to find out how the price, weight and capacity were scaled. Much was learned on how to and not to conduct a survey. A preliminary survey should have been conducted to determine a realistic value of variables. Also many of choices were not close enough together to get a reasonable cut off value. Therefore the data that was produced using conjoint analysis was most likely not as accurate as it could have been. There are some limitations to our model. For the sake of simplicity, the spring was modeled with the length and the spring constant rather than wire thickness, stress, strain and all the other complex analysis that would make the solver take too long to process. By getting a rough idea of what the ranges can be, simple experimentation can be done to prove or disprove this assumption. Future work would consist of a redesign of the spring model to see exactly how much data we may be missing with the assumption that we made with how price, weight and capacity vary with spring length and spring constant. Despite all the assumptions, we still have realized that this product can be very marketable and that the demand is extremely large which means this is a viable design that will yield a high return on an investment.

References

Papalambros, P.Y., and D.J. Wilde, Principles of Optimal Design. 2nd Ed.

Cambridge University Press, New Your, NY, 2000.

Russel, Alastair. “The Changing World of Mobility.” MS Powerpoint Presentation. http://www.airstreamgroup.com/tech/downloads.php

http://www.electricvehiclesnw.com/main/regen.htm http://www.electricstar.org/motorboard.html http://www.hondurasembassy.se/bicycles.pdf http://www.uspto.gov/

Appendix A

Number Made 100,000Selling Price 87.00$

Quantity Cost Total Cost

Warehouse 3000 m^2 20 200,000$ 4,000,000$ Patent International 1 100,000$ 100,000$ Technology Computers, CAD, CNC 1 250,000$ 250,000$ Tooling Costs CNC lathe machine 8 50,000$ 416,667$

Aluminum (6"x3" round stock) 100000 5$ 521,000$ springs 100000 15$ 1,500,000$ sprocket 100000 5$ 500,000$ small sprocket 100000 4$ 400,000$ gears 100000 10$ 1,000,000$ casing 100000 8$ 800,000$ Misc. 100000 5$ 500,000$ Engineering 5 50,000$ 250,000$ Business 4 40,000$ 160,000$ Marketing / Sales 4 42,000$ 168,000$ Assembly 17 25,000$ 416,667$ Machinist 3 25,000$ 69,444$

Yearly Annual Cost: 6,285,111$

Material Cost Price for one52$ 62.85$

Quantity Sold Price (USD) Total Income25,000 87$ 2,175,000$ 25,000 87$ 2,175,000$ 25,000 87$ 2,175,000$ 25,000 87$ 2,175,000$

No. of Units Sold: 100,000 Yearly Income 8,700,000$

=Total Yearly Income - Total Yearly CostYearly Profit: 2,414,889$

Investment (4,766,667)$ Yearly Profit 2,414,889$ Periods 2.16PV Profit 4,766,667$ Difference 0$

Years RBS RBS0 (4,766,667)$ (4,766,667)$ 1 2,414,889$ 2,414,889$ 2 2,414,889$ 2,414,889$ 3 2,414,889$ 2,414,889$ 4 2,414,889$ 5 2,414,889$ 6 2,414,889$ 7 2,414,889$ 8 2,414,889$ 9 2,414,889$

10 2,414,889$ IRR 24.3% 49.8%

3 Years 10 Years

Italy

Break Even Point

Labor (yearly salaries)

GermanySpain

Profit

Rate of Return Method

Data

Description

Cost

RevenueLocation

Materials

Annual Cost

Investment Cost

The Netherlands

Appendix X

Business Plan Outline 1. Company Vision ........................................................................................................... 21 2. Market Analysis ............................................................................................................ 21

2.1 Overall Market ........................................................................................................ 21 2.2 Target Market.......................................................................................................... 21 2.3 Customer Desires .................................................................................................... 21

3. Competitive Analysis.................................................................................................... 23 3.1 Industry Overview .................................................................................................. 23 3.2 Primary Competitors............................................................................................... 23

4. Product Breakdown....................................................................................................... 23 4.1 RBS Optimal Design............................................................................................... 23 4.2 Competitive Analysis of Product ............................................................................ 24

5. Financial Analysis......................................................................................................... 25 5.1 Estimated Costs....................................................................................................... 25 5.2 Projected Revinue ................................................................................................... 26 5.3 Profit ....................................................................................................................... 26

1. Company Vision Millions of people throughout the world use a bicycle as a main means of transportation and our goal is to make sure they all have an effortless ride using the Regenerative Braking System (RBS). The plan is to develop an affordable, energy saving device that is extremely desirable by the day to day biking commuter. This goal will be met by combining a team of highly skilled engineers, market researchers and business specialists and we will yield an extremely profitable product for millions of needy customers.

2. Market Analysis

2.1 Overall Market The projected market size for the RBS is on the order of 700 million people. This number was estimated by the number of people throughout the world who would possibly pay over one hundred dollars for a power assisted biking system. Due to market penetration, this number will be reduced significantly to a value of 100,000 units.

2.2 Target Market The main focus area for this product will be mostly Western Europe due to their great number of biking commuters and high average annual income [1]. It is important to target not only the consumer that will use the product, but also the consumer that will be able to afford the product in the early stages of development. This is to maximize the profit before competition can change the demand curve. 100,000 units will be made every year for three years to introduce the product into the market. After this proving stage, the number of production will be increased or decreased accordingly.

2.3 Customer Desires In order to determine what features the customers desired the most, a survey was given to a small group of mechanical engineering students from the University of Michigan. Even though this is not the ideal group of consumers, their trends were valued and scaled accordingly. The features consisted of price, capacity, and weight. After this survey was collected, a conjoint study was preformed to determine how these features would be weighted. The following data shows the results of this study. Note, this study is limited to the survey size and the range of values. Figures X1-X3 below show these trends.

Figure X1: Weight vs. Utility

Beta vs w eight

y = -0.2164x + 3.2475

0.000

0.500

1.000

1.500

2.000

2.500

5 10 15

lbs

Weight

Linear (Weight)

Figure X: Price vs. Utility

Beta vs Price

y = -0.0529x + 2.7567-3.000

-2.500

-2.000

-1.500

-1.000

-0.500

0.00075 85 95 105

$

Price

Linear (Price)

Figure X: Capacity vs. Utility

Beta vs Capacity

y = 0.0512x - 2.7563

-0.500

0.000

0.500

1.000

1.500

2.000

2.500

50 70 90 110

% Returned

Speed

Linear (Speed)

3. Competitive Analysis

3.1 Industry Overview Despite the trends of modern technology with the automobile, the biking industry is still thriving, meaning that bicycles will be with us for a long time to come. The Airstream group of Canada has show that the growth rates of normal bicycles are 10% per year and surprisingly the growth rate of electric bicycles are 25% per year [2]. This is a very promising statistic and shows that people are leaning towards a more environmentally friendly and healthier lifestyle, which ensures a stable market place for the RBS.

3.2 Primary Competitors Due to the nature of this product, there is nothing on the market right now that has similar capabilities and attributes with in the price range that the RBS can be offered. Therefore the RBS can be modeled as a monopolistic product.

4. Product Breakdown

4.1 RBS Optimal Design The finalized design of the RBS consists of a 25” long compression spring that has a spring constant of 30K N-m that is attached to a 6”max DIA cone via 1/8” wire. The cone is inline with a set of 1” beveled gears. There is a shaft that connects through two of the gears using a clutch that can be engaged when the brakes are being applied. The gear near the sprocket has a free wheel bearing, which allows the bike to both brake and accelerate, using a compact gear train. The sprocket, which is aligned with the free bearing gear, connects to the back sprocket that is mounted on the tire. See Figure 4 for a detailed model.

Figure 4: Schematic of RBS

The majority of the focus of this design is optimizing the spring to meet the needs of the consumer and the producer. Also all other values are so discrete or cannot change and the only flexibility that can be made to the RBS that has any significant value are the spring length and the spring constant. These parameters were optimized to find the spring that can yield the highest profit and yet meet the customer’s needs.

Table 1: Characteristics of the RBS Total Spring Length 18 inches Spring Constant 30K N-m Percent Regenerated ~100% Weight 17 lbs Selling Price $87

4.2 Competitive Analysis of Product The unique concept of our product is the compactness, adaptability and regenerative capability. This allows us to reach a very wide and varied market while meeting the convenience of regenerative braking. We feel that the RBS will thrive in a Western European market due to the lack of immediate competition and the versatility of the product.

Cone Compression Spring

Ratchet

Sprocket

Clutch To Back Tire Freewheel

5. Financial Analysis Overview In this section, we plan to show that not only will the RBS be a good investment, but we will show that the return rate can be extremely rewarding. The quantity of RBSs that will be manufactured is on the order of 100,000 units, with a selling price of $87. Assume that all units are sold in each of the years that they are produced; the break even point is only slightly over 2 years, with an initial investment of 4 million dollars. The rate of return for the investors will be 24.3% over a 3 year period and 49.8% over a 10 year period. See appendix A for full financial analysis.

5.1 Estimated Costs The cost for this total project has many different aspects and must include all facets of cost. Figure 5 shows this expense breakdown:

Figure 5: Investment and Annual Costs

Number Made 100,000Selling Price 87.00$

Quantity Cost Total Cost

Warehouse 3000 m^2 20 200,000$ 4,000,000$ Patent International 1 100,000$ 100,000$ Technology Computers, CAD, CNC 1 250,000$ 250,000$ Tooling Costs CNC lathe machine 8 50,000$ 416,667$

Aluminum (6"x3" round stock) 100000 5$ 521,000$ springs 100000 15$ 1,500,000$ sprocket 100000 5$ 500,000$ small sprocket 100000 4$ 400,000$ gears 100000 10$ 1,000,000$ casing 100000 8$ 800,000$ Misc. 100000 5$ 500,000$ Engineering 5 50,000$ 250,000$ Business 4 40,000$ 160,000$ Marketing / Sales 4 42,000$ 168,000$ Assembly 17 25,000$ 416,667$ Machinist 3 25,000$ 69,444$

Yearly Annual Cost: 6,285,111$

Labor (yearly salaries)

Data

Description

Cost

Materials

Annual Cost

Investment Cost

Mostly all parts of the product are outsourced except for the cone. The cone is manufactured in house on CNC lathes and operated by machinists. Once those parts are produced, the assemblers put them together. The total number of workers were determined by a function of how many units could be produced in a year and how many units are actually made in a year. Some assumptions made were, one machinist can work

three CNC lathe machines at once and each of those machines could produce one cone every 20 minutes. The same types of assumptions were made for the assemblers ending with an end result as shown above.

5.2 Projected Revenue The target consumers are located in Western Europe and are broken up by the following countries [3]. These countries have been researched to have a very large biking commuter population and would be a very good test market to introduce our new product. Given a three year period we can calculate a safe investment plan and a fast break even point. Also another major assumption is that all the units are sold, but this is a fairly safe assumption because of the limited number produced for the given size of each of the markets. The following chart shows the simplified revenue breakdown, Figure 6.

Figure 6: Yearly Revenue in Western Europe

Quantity Sold Price (USD) Total Income25,000 87$ 2,175,000$ 25,000 87$ 2,175,000$ 25,000 87$ 2,175,000$ 25,000 87$ 2,175,000$

No. of Units Sold: 100,000 Yearly Income 8,700,000$

ItalyGermany

Spain

RevenueLocation

The Netherlands

5.3 Profit The yearly profit of the RBS is total yearly revenue – the total yearly profit. Again assuming that all products are sold every year, the net profit for our product will be $2,414,889. Our product has quite a large mark-up, but with our estimations and before competition is introduced, $25 mark-up is not too dangerous. After market penetration, the quantity sold will most likely increase dramatically and other markets will be reached.