VIEWS: 103 PAGES: 18 CATEGORY: Energy & Green Technologies POSTED ON: 9/16/2010
EV refers to the vehicle power supply as a driving force, with the motor drive the wheels moving in line with road traffic, vehicle safety regulations requirements. Because of the smaller environmental impact than conventional cars, is widely optimistic about its prospects, but the current technology is not yet mature.
T H E F U T U R E O F E L E C T R I C C A R S M S & E 2 0 1 Berhane Azage Kazutora Hayashida Nanette Le Rotimi Ojo Farnaz Ronaghi Khameneh 1 1. INTRODUCTION Declaring “For the first time in history, we have set in motion a national policy aimed at both increasing gas mileage and decreasing greenhouse gas pollution for all new trucks and cars,” President Obama recently set in motion a national program aimed at improving fuel efficiency of new cars to an average of 35 miles per gallon (MSNBC). Although not the only policy endorsing the urgency of addressing effects of massive greenhouse emissions, Obama’s policy along with macroeconomic, technological, and structural changes are heralding future cars with much higher fuel efficiency. Strong showing of interest by media, entrepreneurs, venture capitalists, automakers, and even the general public has focused on the need for a highly energy-efficient transportation network that will also have minimal negative externality to our environment. The advent of viable hybrid and electric cars is often seen as viable solution to the demand. The focus of the following paper is then to understand the future of the car market within the U.S. market1 with focus on gasoline and hybrid, electric cars using a dynamic systems model. A. H ISTORICAL B ACKGROUND O F E LECTRIC C ARS To many people’s surprise, electric vehicles (EVs) are not a recent innovation. EVs’ history dates all the way back to 1830s, when the first electric vehicles were assembled in Western Europe and United States (Westbrook, 7). By 1900, the U.S. car market was evenly split between electric cars, steam-powered cars, and gasoline cars (PBS). The “golden-age” of the electric car was nonetheless short-lived. By 1920, due to many factors, including desire for longer distance range, increased horsepower, low price and availability of gasoline, as well as the massive production of substantially lower priced Ford Model T, Electric Cars became a relic of the past (PBS &Westbrook). The modern era signaled interest in Electric vehicles. Following governmental concerns of pollution in late 1960s, and the Arab Oil Embargo of 1973, electric vehicles such as CitiCar showed signs of re-emergence but with very little traction even up to late 1990s (Westbrook, 25-27). Schiffer (2-3) notes there are three dominant theories for the failure of Electric Vehicles in the modern era. The first is Vested Interest Theory, which notes that desirable products can be prevented from reaching markets by actions of powerful corporations’ such as GM’s lack of commitment in the success of the infamous EV1 vehicles. Such factor is not restricted to lack of commitment to making a vehicle cool, reliable, appealing, but also to governmental commitment in upholding certain legislation. The EV1 came to being only due to a need by GM to meet governmental restrictions such one legislated by California Air Resources Board (CARB) which was later relaxed due to Automakers’ pressure.2 The second is the Technological Constraint Theory, that posits that technological constraints, particularly range and power restrictions deriving from inability of battery technology to surpass gasoline’s advantage of high energy density, has been a major source of failure for expansion of electric vehicles. A third theory is that the products available were simply not meeting consumer performance needs. That is, products were not cool enough to be adopted by the public and the ease of access to supporting infrastructure of a given product was not present. In essence, not many electric cars can be produced without the proper charging stations, battery manufacturing facilities, and etc. that are necessary for its adoption. These three theories are by no means are complete, but their inner relationship and effect is undeniable and worth exploring. Understanding past failures should provide a rubric of understanding the current events surrounding electric vehicles. As a result, we have identified the coolness factor, infrastructural support, intrinsic quality of product, as well as governmental and corporate commitment as key factors that have often determined the success or failure of Electric Vehicles. B. R ECENT T RENDS A ND B ACKGROUNDS Three major recent trends seem to indicate that the future of electric cars maybe nearby. First, Since 1970s, concern about climate change has been prevalent, but a consensus on the level of impact and the need to change has not been as strong as in the last decade. In reality, in 1990, the Second World Climate Conference adopted the Climate Change Convention, which “called climate change as a "common concern of humankind"” (Earth Summit +5). Alarming Greenhouse emissions have prompted many governments to commit large amounts of research funding and companies are responding in anticipation of future clean energy market (CNET News). Second, technological revolutions as well as general interest in Hybrid/Electric 1 Justification for Choice of U.S. Market is provided in Appendix 2 Two percent of light duty vehicle sales in CA must be zero emissions by 1998 2 Azage, Hayashida, Le, Ojo, Ronaghi vehicles as solutions to the emissions problem appear to have drawn the interest of investors and businesses. Several promising companies, such as Tesla Motors with its battery technology and Better Place with its project of providing charging infrastructure, have attracted partnership from major automakers such as Renault (CSR Europe). Concurrently, clean tech has been a new investment trend in the venture world; with much focus various alternative energy technologies, including electric and hybrid vehicles. Hydrogen cars have proven to be unviable at this point due to the high economic and technical costs for producing them, and the bad benefit-cost ratio for producing hydrogen cars (Shinnar) and we expect such benefit-cost analysis to continue for future products. Third, recent trends on hybrid car adoption in the mainstream along with well- designed future Electric cars such as Tesla’s Roadster and the Volt indicate an increasing notion of acceptability for hybrid/electric cars. Therefore, the focus of the paper is on relationship of gasoline, hybrid and electric. Exploring technological improvement, funding levels and legislation that show governmental commitment, infrastructural changes, as well as attractiveness of products that are available will provide us valuable insight into the dynamic future of the car market. 2. DYNAMIC MODEL FOR THE FUTURE OF ELECTRIC CARS A. E QUATIONS A ND D YNAMIC M ODEL D ESCRIPTION To model the dynamics of electric cars market we use a modified competition model. We divide the potential car market into three different segments namely: low-income, middle-income, and high-income. Carmakers usually have different products for each income segment. The acceptability or intrinsic quality of a product P offered by a company to a consumer for a given market segment i is described by: (Eq. 1), where a is an attribute vector describing the normalized magnitude3 of a products principal attribute. w is a vector of the weights of each attribute normalized with respect to 1. Our attribute vector consists of a car’s initial price, running cost, performance, environment friendliness, and infrastructure support. Our initial approach was to expand the “new game in competition” to describe the dynamics of three competing brands but ended up with analytically intractable systems of equation. We therefore decided to create a hybrid model that combines elements of “new game in competition” with that of a generic competition model. For any given income segment, let G show the number of gasoline cars, E show number of electric cars and H show number of hybrid cars respectively. We derive the system below: (Eq. 2) represents the intrinsic growth of a product in the absence of competition, while depicts the mutual interference constants describing the effects of company I with strategy , and coolness factor q, on its’ competitors.(i.e. they are a scalar multiple of the acceptability of company’s product from Eq. 1). (t) shows additional control measures employed by company I that are not reflected in the acceptability of a product to a consumer or policies implemented by the government that benefits I such as subsidies, tax breaks, etc. For instance, the government can foster a program that would put a certain number of electric cars for public transportation. Quantitatively, at a particular time, we can set C(t) to be an impulse that would bolster the growth rate of a certain product I. Setting shifts the phase portrait and alters the marginal limit of I by a factor dependent on k. This transformation increases the marginal limit of I’s market share by k but does not alter the general behavior of the system for an impulse signal (i.e. we control with a constant input or only input at one time interval). 3 Normalization: a=[attribute1/max (attribute1) ; attribute2/max (attribute2)…] 3 Azage, Hayashida, Le, Ojo, Ronaghi B. A NALYTICAL S OLUTIONS To understand the general behavior, we can first assume that (t) = 0 and independent of i, and set the derivates to zero, we immediately identify the equilibrium points4 , and the intersection of the planes: (Eq. 3) By evaluating the Jacobian of Eq. 2 we obtain the linear system: C1. V ISUALIZATION A ND L EVEL S ETTING P ROPOSAL For example, setting and generates the 3D vector field shown in Fig 1 and 2: Fig 1. Fig 2. Visualization limitations associated with working in 3D makes the direct interpretation of the phase portrait very difficult. The only obvious conclusion we can derive from this image in that the axis with the greatest eventually dominates the market. Additionally, these figures shows that we can come to reasonable conclusions by setting the level of an arbitrary axis and quantitative analyzing the behavior of the other two axes. Since Gasoline Cars currently dominate the market and we are mainly concerned with the future of electric cars, we will proceed to analyze their dynamic behavior by level setting the Hybrid dimension. Simulation analysis is also provided to illustrate the competition amongst all three car types. Consequently, for phase plot illustrations, we set H = f, such that , and we obtain the following dynamics: 4 This model potentially has infinitely many equilibrium points! 4 Azage, Hayashida, Le, Ojo, Ronaghi (Eq. 4) Eq. 4 has the effect of reducing the marginal limits of both Gasoline and Electric car’s respective market shares by . This implies that the pattern of behavior at every level set of H is similar, which assumes H is static and hence the growth rate of H is 0. However, H of course is itself often dynamic, so analysis using only phase portrait is limiting but remains insightful. Therefore, we have used matlab simulation to demonstrate the behavior when H is both dynamic and static. C2. S TATIC A NALYSIS W ITH S IMULATION A ND P HASE P ORTRAITS ( I.E. H ’(T)=0) The figure below shows the approximate behavior of our system at every level set of H excluding the point where H is max which is an equilibrium point, and arbitrary values of and Fig 3. [G’=G(1-G-2E), E’=E(1-E-3G)] Fig 4. [G’=G(1-G-0.5E), E’=E(1-0.5G-E)] Fig. 5 [G’=G(1-G-0.75E), E’=E(1-E-2G)] Fig. 6 [G’=G(1-G-2E), E’=E(1-E-0.75G)] Fig. 7 [G’=G(1-G-0.5E), E’=E(1-E-2G)] Fig. 8 [G’=G(1-G-2E), E’=E(1-E-0.5G)] The G null cline is the orange line defined by and G=0 while the E null cline is the yellow line defined by and E=0. A line of separatrix defined by bold red arrow passes through the point of intersection of both nullclines. Any trajectory originating at a given side of the separatrix stays on that side the separatrix, while trajectories originating on the separatrix always end up at the point of intersection of the G and E nullclines. Intersection of the two null clines equals to (Gnl,Enl) such that If Gnl is negative, G will always win (Fig. 5). If Enl is negative, E will always win without respect to initial condition (Fig. 6). Due to the characteristics of the null clines, Enl and Gnl cannot be simultaneously negative. If Enl and Gnl are both positive, then 5 Azage, Hayashida, Le, Ojo, Ronaghi we either have a saddle point (Fig. 1) when either or is greater than 1 or an equilibrium point (Fig. 5) if both and are less than 1. When , then we have two parallel null clines. In such case, the car type with the larger interference factor will eventually win. That completes all possible major combinations for phase portraits. Phase portraits are very informative for a static Hybrid case, and a simulation is not necessary for H’(t)=0 as it is not as comprehensive. Nonetheless, we did run simulations to test our phase portrait results. The lesson from the phase portraits is that given a very dominant gasoline car market that is the reality of our current times, the ways that electric car can win is if it always has a better product/strategy, including quality of product, infrastructure, perception driven by advertising and other factors as described in modeling section, and/or through our control input. C3. D YNAMIC A NALYSIS W ITH S IMULATION ( I.E. H ’(T) I S N OT A LWAYS Z ERO) Making H(t) dynamic makes visualization and processing of phase portraits difficult. Simulations nonetheless require a huge range of possible values. We have conducted many test runs, and have included summary of insightful graphs below. We assumed our current potential market N will be 300 million passenger and light truck cars. We expect our rg,rh,re to grow at historical annual growth rate of 2% and will behave similarly in terms of adjustment to increase rate of growth for an early stage vs. later stage. We assumed a variety of initial G,H,E. The reason for our assumption is that we can have an impacting shift in initial condition depending on our control input, and having an E=0 does not provide much room for analysis of future of electric car either. So we used some reasonable (G0,H0,E0 ) of (0.8,0.1,0.05), (0.6,0.2,0.1) and ( , , ) of (3,2,1) ,(1,3,2), (2,3,1), (1,1,3). Simulations for (G0,H0,E0 ) = (0.8,0.1,0.05) Fig. 9 ( , , ) of (3,2,1) Fig. 10 ( , , ) of (1,3,2) Fig. 11 ( , , ) of (2,3,1) Fig. 12 ( , , ) of (1,1,3) As expected, with a high market share, and a dominating strategy (Fig. 9) or close enough (Fig. 11) (just like past historical cases), gasoline car continues to dominate. However, as shown in Fig. 10 and Fig. 12, if either hybrid car or electric car has a significantly more dominant strategy, combined with infrastructure, acceptability as well as other factors that enhance its ability to interfere, then Electric car or Hybrid car will win. We think Electric car can win as once battery technology improves, and needed infrastructure and services are available, the hybrid car will lose out in its environmental friendliness as it is not a zero emission machine, and has a redundant engine. Such acknowledgment of course cannot definitively be determined now Simulations for (G0,H0,E0 ) = (0.6,0.2,0.1) Fig. 13 ( , , ) of (3,2,1) Fig. 14 ( , , ) of (1,3,2) Fig. 15 ( , , ) of (2,3,1) Fig. 16 ( , , ) of (1,1,3) 6 Azage, Hayashida, Le, Ojo, Ronaghi 3. CONCLUSION Currently, there are about 247 million registered gasoline cars (which is about 83% of overall potential market). There are 1.3 million hybrid cars on the road, accounting for .43% of the market. We assume that a control input, such as a government pilot project of electric fleet can introduce into the market about 300,000 electric vehicles at some point in time, which makes the Electric vehicle share to be 8.33%. Using such data and analysis on current available products and estimations of our factors (refer to appendix for detail), we have come up with a winning strategy for electric car. As shown in our previous simulations, our model predicts that it is impossible for Electric Cars to dominate the market by offering an equally or marginally superior product. The winning strategy will then have to rely on governmental support to jumpstart it through our control, and then the natural dynamics provided by maximizing with respect to and . Fig. 17 From available data we have estimated (see Appendix) 1.06. We also estimated to be 0.81. Our task is a value of , such that for which trajectory passing through (G, E) = (.83N,0.0043N,0.001N) terminates at . We can numerical verify that (Fig 17) satisfies the conditions. Details for configuration of a product that achieves such number is provided in appendix. The table in appendix shows that even with superior and less expensive product line Electric cars needed some cool factor or substantial governmental support to cause enough interference in the growth of gasoline cars as to eventually dominate the market. Clearly early models for the introduction of electric cars failed in almost all of the above respect. As Fig. 17 demonstrates, Hybrid cars increase in number, but eventually plateau, further purporting the argument that hybrid car will be a redundant and less superior product if a great electric car with the appropriate infrastructural support and product quality can be produced. As our analysis has shown, given the initial distribution of the market, the success of Electric cars within the future intrinsically much depends on the strategies pursued and is responsive to governmental incentives and environmental programs to jumpstart its growth. We have provided a more detailed set of recommendations and strategies to companies and governments based on the analysis of our dynamic model in the appendix as well. 7 Azage, Hayashida, Le, Ojo, Ronaghi WORK CITED AND CONSULTED • Auto Pricing. <http://www.domesticsale.com/autoclassified/prices.html> • Bureau of Transportation Statistics. Household and Demographic Characteristics, National transportation Statistics, Distribution of Households by Number of Household Vehicles, for Each Income Class. 2001-2007. http://www.bts.gov/publications/ • CNET News. “Obama commits $1.2. billion in energy R&D.” 23 March, 2009. < http://news.cnet.com/8301-11128_3-10202041-54.html> • Consumer Reports. Car Ownership Costs. <http://www.consumerreports.org/cro/cars/pricing/what- that-car-really-costs-to-own-4-08/overview/what-that-car-really-costs-to-own-ov.htm> • CSR Europe. “Renault-Nissan and Project Better Place prepare for first mass marketed electric vehicles." 28 January, 2008. < http://www.csreurope.org/news.php?type=&action=show_news&news_id=1094> • Edmunds. Auto Pricing and Specs Information. <http://www.edmunds.com/> • Earth Summit +5. “Combating Global Warming: The Climate Change Convention." United Nations Department of Public Information. 1997. June 1997 < http://www.un.org/ecosocdev/geninfo/sustdev/climate.htm> • HybridCars. Profile of Hybrid Drivers and Sales Data. 2006. http://www.hybridcars.com/hybrid- drivers/profile-of-hybrid-drivers.html • MSNBC. “Obama unveils mpg rule, gets broad support.” May 19, 2009. <http://www.msnbc.msn.com/id/30810514/> • National Automobile Dealers Association. NADA Data- Sales Data and Growth Rate. 2008. < http://www.nada.org/NR/rdonlyres/0FE75B2C-69F0-4039-89FE- 1366B5B86C97/0/NADAData08_no.pdf> • PBS.Org. “Timeline: Life & Death of the Electric Car.” 06/09/2006. <http://www.pbs.org/now/shows/223/electric-car-timeline.html> • Westbrook, M. “History of Electric Cars Upto 1990.” The Electric Car. Institution of Engineering and Technology Power and Energy Series 38: 2001. • Schiffer, et. Al. Taking Charge: The Electric Automobile in America. Smithsonian Institution Press: 1994. • Shinnar, Reuel. The hydrogen economy, fuel cells, and electric cars, Technology in Society, Volume 25, Issue 4, November 2003, Pages 455-476. <http://www.sciencedirect.com/science/article/B6V8049V78GW- 2/2/6eb71592d4f10e12ced3050d687dc999> • U.S. Department of Labor. Current Population Survey. 2007. <http://www.census.gov/> 8 Azage, Hayashida, Le, Ojo, Ronaghi APPENDIX 1. WHY T HE U .S. C AR M ARKET? Our focus is on the U.S. vehicle market because we have a free-market economy as opposed to countries like China, where all vehicles could be the same if the Chinese government decided to do so. Our model will analyze a people’s true preferences towards owning a hybrid or electric car. This can only be done in a free-market economy where each consumer is allowed to express their preference on these alternative fuel vehicles. Furthermore, there is much more data on the U.S. vehicle market. 3. S TRATEGY D ISCUSSION A. T able 1 . W inning S trategy C onfiguration for E lectric C ar Coolness Electric = 5 Gas = 3 Hybrid Strategy 5 3 Low Income: Initial cost 13000 13742 22751.25 Running cost 30000 33888 37527 Performance + 130 120 120 Environment + 70 27.33 45 Infrastructure + 3 1 3 Middle Income: Initial cost 35000 38154 40129 Running cost 45000 47973 57044 Performance + 160 160 160 Environment + 70 19.25 31 Infrastructure + 3 1 2 High Income Initial cost 75000 86717 80012 Running cost 90000 11247 103054 Performance + 180 180 180 Environment + 50 15 26 Infrastructure + 3 1 2 9 Azage, Hayashida, Le, Ojo, Ronaghi Cross Model Interference 2.91 1.05 0.81 Table 1. Winning Strategy. B. N otes o n S trategies for G overnments a nd C ompanies The U.S. government can push the market to shift towards hybrid and electric cars that the market takes off and reach its equilibrium on its own. With this model, the U.S. government can determine how much pressure they can place on the market before it takes off on its own. After a period of time, through word-of-mouth, the coolness factor, peer pressure, etc., hybrid and electric cars will play a competitive role in the vehicle industry. Once hybrid and electric cars have a large enough presence in the market, the cost to manufacture and produce them will decrease significantly and the U.S. government will be able to lift their incentives. At this equilibrium point, there would be little to no deterring factors for consumers to purchase these alternative fuel vehicles. Another motivating incentive is for environmental programs to reward bonuses to consumers who trade in their gasoline cars for an alternative fuel vehicle. This will also promote the market movement towards hybrid and electric vehicles. Bonuses give consumers the opportunity to apply it towards the high initial cost of the hybrid or electric car. Thus, a bonus would have the same affect on the market as a U.S. government subsidy. I. S TRATEGIES T HAT T HE C OMPANIES T O E NCOURAGE S WITCH • Favorable Trade-in's for Gasoline Cars: Used/New car dealers associated with the manufacturer can provide services where a driver can trade in his current gasoline car and get an electric vehicle from the same manufacturer under favorable conditions, including warranty, price, maintenance, etc. • Provide EV's for Rental Cars/Fleet Services: One reason that's inhibiting consumers from buying EV's is due to their lack of knowledge and trust in EV's. Manufacturer can provide EV's for fleet services so that consumers will get first-hand experience of the technologies. II. S TRATEGIES T HAT T HE G OVERNMENTS C AN T AKE • Tax incentives for EV's: As the US government did for hybrid vehicles; they can implement a similar tax incentive for consumers who purchase electric vehicles. • Subsidies for EV technologies: One of the obstacles that prevent normal consumers from purchasing electric vehicles is the high initial cost. However, with government's subsidies for key EV technologies, such as batteries, the price tag can be driven down to the level that normal consumers will be able to afford. 3. S IMULATION C ODE SIMULATION CODE: clear; %Set Up year=200; period=365; % Weekly maxtime = period*year; halftime=maxtime/2; N = zeros(maxtime, 1); G = zeros( maxtime , 1 ); H = zeros( maxtime , 1 ); E = zeros( maxtime , 1 ); dG = zeros( maxtime , 1 ); dH = zeros( maxtime , 1 ); dE = zeros( maxtime , 1 ); alpha_G= ones(maxtime , 1); alpha_H= ones(maxtime , 1); alpha_E= ones(maxtime , 1); %Initial Conditions N(1) = 300e6 ; 10 Azage, Hayashida, Le, Ojo, Ronaghi G(1) = 0.83*N(1); %Current Level is 247 million cars H(1) = 0.044*N(1); %Approximate, but very close to current level of 1.3 million hybrids E(1) = 0.1*N(1); %Needs one big push to achieve 2.5 million Electric Cars, Reasonable %Natural Growth Rate for Period avg_year_rate=2e-2; mod_factor_g=N(1)/G(1); mod_factor_e=N(1)/E(1); mod_factor_h=N(1)/H(1);% When something is small, it will grow faster than usual. RG = ((1+avg_year_rate*mod_factor_g)^(1/period)-1); RH = ((1+avg_year_rate*mod_factor_h)^(1/period)-1); RE = ((1+avg_year_rate*mod_factor_e)^(1/period)-1); %Strategy alpha_G(1:maxtime)=1.06; alpha_H(1:maxtime)=1.0; alpha_E(1:maxtime)=2.9; % Dynamics for i=2 : maxtime dG(i) = RG * G( i-1 )*( 1 - G( i-1 )/N(i-1) - alpha_H( i ) * H( i-1 )/N(i-1) - alpha_E( i ) * E( i-1 )/N(i-1) ) ; dE(i) = RE * E( i-1 )*( 1 - E( i-1 )/N(i-1) - alpha_H( i ) * H( i-1 )/N(i-1) - alpha_G( i ) * G( i-1 )/N(i-1) ) ; dH(i) = RH * H( i-1 )*( 1 - H( i-1 )/N(i-1) - alpha_G( i ) * G( i-1 )/N(i-1) - alpha_E( i ) * E( i-1 )/N(i-1) ) ; G( i ) = G( i-1 ) + dG(i) ; H( i ) = H( i-1 ) + dH(i) ; E( i ) = E( i-1 ) + dE(i) ; mod_factor_g=N(1)/G(1); mod_factor_e=N(1)/E(1); mod_factor_h=N(1)/H(1);% When something is small, it will grow faster than usual. RG = ((1+avg_year_rate*mod_factor_g)^(1/period)-1); RH = ((1+avg_year_rate*mod_factor_h)^(1/period)-1); RE = ((1+avg_year_rate*mod_factor_e)^(1/period)-1); N(i) = N(i-1); end %PLOTTING t=(0:1/period:year-1/period).'; plot(t , H , 'g'); hold on plot(t , G , 'r'); hold on plot(t , E , 'b'); hold off xlabel('Time '); ylabel('# of Cars'); legend('Hybrid','Gasoline','Electric'); 11 Azage, Hayashida, Le, Ojo, Ronaghi TABLES AND SUPPORTING DATA Table 2: Population and Car Market 1. Potential Market of Adults Proposed Segments by Segments (income/Worker) Income/Person # of Potential Customers Low $0-$25,124 50,635,856 Middle 25124-$56047 50,066,696 High $56,047and above 50,360,331 2. Estimate of Electric/Hybrid Passenger Car and Light Truck Users Total Hybrid/Electric Cars 1320800 Total # of Cars 248700997 Total Gasoline Cars 247380197 Refer to 2-4 Segments Percentage Distribution # of Cars Low 0.2 264,160 Middle 0.23 303,784 High 0.75 990,600 Assumed that # of Hybrid Vehicle Ownes in the High Income Category Make up more than ~(0.71+0.42)/2=56%, so I am using about 75% to include people making >$75,000 http://www.hybridcars.com/hybrid-drivers/profile-of-hybrid-drivers.html 3. Estimate of Gasoline Car Users (Refer to 2-4) # of Gasoline Cars in Segments Average # of Cars/Person Segment Low 1.068574333 62,939,769 Middle 1.370071161 80,698,142 High 1.761308391 103,742,286 12 Azage, Hayashida, Le, Ojo, Ronaghi Table 3: GASOLINE INITIAL & RUNNING COST, SPECIFICATIONS Price Fuel efficiency Running Cost Luxury 2009 Lexus LS $56,803 - 24 (Est) mpg Hwy, 16 $98,166 56803 94370 75586.5 16 $94,370 (Est) mpg City 2009 Mercedes $89,350 22 (Est) mpg Hwy, 14 $123,78 89350 89350 14 S (Est) mpg City 2009 Cadillac $86,215 - 24 (Est) mpg Hwy, 15 $115,45 86215 104215 95215 15 XLR $104,215 (Est) mpg City Average 86717.17 15 $112,47 86717 15 Middle 2008 Audi A3 $25,930 - 21 (Est) mpg City $52,193 25930 34915 30423 21 Income $34,915 2008 Buick $24,250 - 17 (Est) mpg City $51,987 24250 32380 28315 17 LaCrosse $32,380 2010 Chevrolet $22,245 - 17 (Est) mpg City 22245 33430 27838 17 Camaro $33,430 2009 Honda $20,905 - 22 (Est) mpg City $39,740 20905 31155 26030 22 Accord $31,155 Average 28151.25 19.25 $47,973 28151 19 Low Hyundai $10,775 - 32 (Est) mpg Hwy, 27 $33,261 10775 15595 13185 27 Income Accent 2008 $15,595 (Est) mpg City 2009 Chev $11,965 - 27 (Est) mpg City $33,921 11965 14100 13032.5 27 Aveo $14,100 2008 Honda Fit $13,950 - 28 (Est) mpg City $34,482 13950 16070 15010 28 $16,070 Average 13742.5 27.33 $33,888 13742 27 3 13 Azage, Hayashida, Le, Ojo, Ronaghi Table 4: HYBRID INITIAL COST, RUNNING COST, SPECIFICATIONS HYBRID CARS (edmunds.com) MSRP (Manufacturer's True EPA - City EPA - Suggested Retail Price) Cost to Highway Own (5 year total) Honda Insight 19800 Toyta Prius 22000 $38,818 48 45 Honda Civic 23650 $37,289 40 45 Chevrolet Malibu 25555 Toyota Camry 26150 $48,866 33 34 Saturn Aura 26325 Ford Fusion 27270 Mazda Tribute 28175 Ford Escape 29645 $45,406 34 31 Mercury Mariner 30090 $47,402 34 31 Lexus HS 32000 GMC Sierra 38390 Toyota Highlander 41020 $53,294 27 25 Lexus RX 42000 Lexus LS 42080 Dodge Durango 45040 Chrysler Aspen 45070 $60,172 20 22 Chrysler Silverado 47305 $60,614 21 22 Chevrolet Tahoe 50455 $75,381 21 22 GMC Yukon 50920 Lexus GS 56550 Cadillac Escalade 73135 $103,054 not listed not listed Mercedes Benz S Class 110350 14 Azage, Hayashida, Le, Ojo, Ronaghi Table 5: 1990 1991 1992 1993 1994 1995 1996 1997 19 Highway, total (registered 193,057,376 192,313,834 194,427,346 198,041,338 201,801,921 205,427,212 210,441,249 211,580,033 215,4 vehicles) Passenger car 133,700,496 128,299,601 126,581,148 127,327,189 127,883,469 128,386,775 129,728,341 129,748,704 131,8 Light Trucks 48,274,555 53,033,443 57,091,143 59,993,706 62,903,589 65,738,322 69,133,913 70,224,082 71,3 Total 181,975,051 181,333,044 183,672,291 187,320,895 190,787,058 194,125,097 198,862,254 199,972,786 203,1 Growth Rate -0.35% 1.29% 1.99% 1.85% 1.75% 2.44% 0.56% Average(Last 10 years) 1.79% Projections 2007 2008 Passenger/Light Truck 238,731,945 243,014,645 http://www.bts.gov/publications/national_transportation_statistics/html/table_01_11.html NADA predicts it is nearly 248 million, using that number now. http://www.nada.org/NR/rdonlyres/0FE75B2C-69F0-4039-89FE-1366B5B86C97/0/NADADa numbers are not off. 15 Azage, Hayashida, Le, Ojo, Ronaghi Table 6: HYBRID CARS SOLD YEAR # of Cars Sold 1999 0 2000 9500 2001 20,300 2002 35,000 2003 48000 2004 88000 2005 200000 2006 250,000 2007 350,000 2008 320,000 Total 1320800 Sources http://www.hybridcar.com/index2.php?option=com_content&do_pdf =1&id=66 http://www.hybridcars.com/files/dec08-us-total-sales.gif http://www.bts.gov/publications/journal_of_transportation_and_stati stics/volume_05_number_23/html/paper_02/table_02_01.html 16 Azage, Hayashida, Le, Ojo, Ronaghi Table 7 - Distribution of Households by Number of Household Vehicles, for Each Income Class Household income Number of Household Vehicles 0 vehicles 1 vehicle 2 vehicles 3 or more Total Percent vehicles Percent SE Percent SE Percent SE Percent SE 0-24,999 19.5 0.61 47.9 0.73 22.2 0.53 10.4 0.41 100.0 25,000-49,999 3.3 0.29 33.7 0.61 40.6 0.54 22.5 0.51 100.0 50,0000-74,999 1.4 0.23 20.6 0.69 45.7 0.85 32.4 0.65 100.0 75,000-99,999 0.8 0.24 11.8 0.89 47.9 1.22 39.5 1.02 100.0 100,000 + 1.3 0.26 9.6 0.66 48.2 1.10 40.9 0.98 100.0 Overall 7.2 0.20 30.8 0.31 37.7 0.26 24.3 0.24 100.0 Note: Sample covers about 26 thousand households, SE = standard error. Numbers may not add to 100 percent due to rounding. Source: Calculated from the 2001 National Household Travel Survey, Household File, U.S. Department of Transportation, Bureau of Transportation Statistics and Federal Highway Administration. http://www.bts.gov/publications/journal_of_transportation_and_statistics/volume_05_number_23/html/paper_02/table_02_01.html 17 Azage, Hayashida, Le, Ojo, Ronaghi Table 8: INCOME LEVELS Total 116783 Average U.S.Worki 151,062,8 Avg # of People/Household 1.293545 Household ng Age Cumulati83 # of Income/Wor Income Levels, Number of Households 95 # of workers Source: Percentag Populatio ve 0 0 Workers ker Under $2,500 2420 2.07% 3,130,381 (factfinder.census. 2.07% e (16+) n 2.07% $ 2,500 to $ 4,999 993 0.85% 1,284,491 0.85% 2.92% 3,130,381 gov) $ 5,000 to $ 7,499 1868 1.60% 2,416,344 1.60% 4.52% 4,414,872 $ 7,500 to $ 9,999 3174 2.72% 4,105,715 2.72% 7.24% 6,831,216 $10,000 to $12,499 3565 3.05% 4,611,491 3.05% 10.29% 10,936,93 $12,500 to $14,999 3486 2.99% 4,509,301 2.99% 13.28% 15,548,42 1 $15,000 to $17,499 3753 3.21% 4,854,678 3.21% 16.49% 20,057,72 2 $17,500 to $19,999 2974 2.55% 3,847,006 2.55% 19.04% 24,912,40 3 $20,000 to $22,499 3731 3.19% 4,826,220 3.19% 22.23% 28,759,40 1 $22,500 to $24,999 3070 2.63% 3,971,186 2.63% 24.86% 33,585,62 7 $25,000 to $27,499 3728 3.19% 4,822,339 3.19% 28.05% 37,556,81 7 $27,500 to $29,999 2586 2.21% 3,345,110 2.21% 30.27% 42,379,15 3 $30,000 to $32,499 3797 3.25% 4,911,594 3.25% 33.52% 45,724,26 2 25123.9626 $32,500 to $34,999 2421 2.07% 3,131,675 2.07% 35.59% 50,635,85 2 $35,000 to $37,499 3384 2.90% 4,377,359 2.90% 38.49% 53,767,53 6 $37,500 to $39,999 2404 2.06% 3,109,684 2.06% 40.55% 58,144,89 1 $40,000 to $42,499 3548 3.04% 4,589,501 3.04% 43.59% 61,254,57 0 $42,500 to $44,999 2202 1.89% 2,848,388 1.89% 45.47% 65,844,07 5 $45,000 to $47,499 2906 2.49% 3,759,045 2.49% 47.96% 68,692,46 6 $47,500 to $49,999 2077 1.78% 2,686,695 1.78% 49.74% 72,451,50 4 $50,000 to $52,499 3256 2.79% 4,211,786 2.79% 52.53% 75,138,20 9 $52,500 to $54,999 1927 1.65% 2,492,663 1.65% 54.18% 79,349,98 4 $55,000 to $57,499 2595 2.22% 3,356,752 2.22% 56.40% 81,842,65 9 $57,500 to $59,999 1787 1.53% 2,311,567 1.53% 57.93% 85,199,40 2 $60,000 to $62,499 2789 2.39% 3,607,700 2.39% 60.32% 87,510,97 4 $62,500 to $64,999 1659 1.42% 2,145,993 1.42% 61.74% 91,118,67 1 $65,000 to $67,499 2112 1.81% 2,731,969 1.81% 63.55% 93,264,66 0 $67,500 to $69,999 1449 1.24% 1,874,348 1.24% 64.79% 95,996,63 3 $70,000 to $72,499 2189 1.87% 2,831,572 1.87% 66.66% 97,870,98 2 56046.7141 $72,500 to $74,999 1505 1.29% 1,946,787 1.29% 67.95% 100,702,5 0 $75,000 to $77,499 1998 1.71% 2,584,505 1.71% 69.66% 102,649,3 52 $77,500 to $79,999 1314 1.13% 1,699,719 1.13% 70.79% 105,233,8 39 $80,000 to $82,499 1872 1.60% 2,421,518 1.60% 72.39% 106,933,5 44 $82,500 to $84,999 1220 1.04% 1,578,126 1.04% 73.44% 109,355,0 63 $85,000 to $87,499 1573 1.35% 2,034,748 1.35% 74.78% 110,933,2 81 $87,500 to $89,999 1123 0.96% 1,452,652 0.96% 75.74% 112,967,9 07 $90,000 to $92,499 1566 1.34% 2,025,693 1.34% 77.08% 114,420,6 55 $92,500 to $94,999 987 0.85% 1,276,730 0.85% 77.93% 116,446,3 07 $95,000 to $97,499 1216 1.04% 1,572,952 1.04% 78.97% 117,723,0 00 $97,500 to $99,999 972 0.83% 1,257,327 0.83% 79.80% 119,295,9 30 $100,000 and over 23586 20.20 30,509,575 20.20% 100.00% 120,553,3 82 Total 116782 100.00 % 151,062,883 100.00% 200.00% 151,062,8 08 Income Segmentation (#Population, Households in % 302,125,7 83 Standard Income -Wages and Salaries thousdands) 66 tp://www.census.gov/macro/032008/rdcall/ Reported Before Tax- A good indicator for 1_001.htm, discretionary spending that amount of Data as of 2007 will be available after taxes, credits, and other forms of expenses 18
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