Article Template for the EVS27 Symposium

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1 EVS27 Barcelna, Spain, Nvember 17-20, 2013 Article Template fr the EVS27 Sympsium Pierre Ducharme 1,4, Simn Ouellette 3 1 Pierre Ducharme, MARCON, pducharme@marcn.qc.ca 2 Simn Ouellette, CrssChasm Technlgies, suellette@crsschasm.cm, Abstract The number f ptins available t transit fleets is grwing and the pressures t select the ptimal prpulsin technlgy are als increasing. Given that there is n ne ptimal bus fr an entire transit system, there s a need t ptimize the fleet, identifying the mst apprpriate mix f technlgies reflecting the system s requirements and realities. This presentatin will discuss factrs t be evaluated as well as the measurement and analytical technlgy enabling bjective calculatins n a per rute basis. This 360 analysis facilitates the ptimal prpulsin technlgy purchase decisin and demnstrates the validity f electric bus technlgy. Keywrds: alternate fuel bus, bus fleet ptimizatin, rute characterizatin, duty cycle, fuel cnsumptin 1 Intrductin The backbne f urban public transprtatin in Nrth America has been the autnmus bus fr a very lng time. Subways are expensive and cmplex t build, particularly in a densely ppulated area where they are mst needed. Aerial trains are aesthetically unppular and land based nes are space cnstrained where rights-fway have nt been planned lng ag. Tramways and trlley buses require a netwrk f wires that is als difficult t sell t the public, particularly when they have nt traditinally been part f the urban landscape. As a result, well ver 50% f all public transprtatin trips are cmpleted by bus with heavy rail ranking a distant secnd at a third f the trips and light and cmmuter rail representing less than 5% f annual urban trips each. Thanks t greater envirnmental awareness and the rising price f fuel, public transprtatin usage is grwing in Nrth America, limited nly by public funding fr vehicles, infrastructure and system peratins. Buses are likely t retain the largest share f the market as they are quickly put in service and very flexible when time cmes t deply them n the grund. This certainly has been the case ver the last decade with diesel electric hybrid buses making very significant inrads in the urban transit fleet acrss the cntinent. But mre recently, the abundance and cnsequently very lw price f natural gas are making CNG and LNG buses even bigger cmpetitrs that they were nly a few mnths ag with their sales nw grwing faster than thse f electric buses. It is still early t tell whether CNGelectric hybrid bus sales will ever pick up frm their dismal perfrmance t date. But the cmplexity f selecting the right vehicles and ptimising the vehicle mix in the fleet is als grwing with the arrival f multiple prpulsin technlgies n the market. Such cmplexity and the lack f familiarity f mst transit peratrs with electric vehicles makes it harder fr electric and hybrid-electric buses t make significant inrads in the urban transit industry. EVS27 Internatinal Battery, Hybrid and Fuel Cell Electric Vehicle Sympsium 1

2 2 The Challenge In Nrth America, Natinal (in the USA) and/r State/Prvincial gvernments heavily subsidize the acquisitin cst f urban transit vehicles by private peratrs and/r municipal/lcal gvernments wh are respnsible fr perating expenses such as fuel, maintenance and manpwer. Fleet managers therefre have a strng incentive t select vehicles with lw fuel cnsumptin, lw cst fuel and lw maintenance csts. The added bnus is that lw fuel cnsumptin usually translates int lw carbn ftprint. These factrs, fuel and maintenance, added t reliability f the vehicles, define perfrmance in the mind f transit fleet peratrs. But the perfrmance f any vehicle is highly dependent n its usage. In the language f fleet peratrs, usage is largely synnymus with duty cycle. S, in the past, managers used several typical duty cycles t benchmark their fleet against a few industry standards. The tw main variables in determining a duty cycle are the average speed f the bus and the number f stps it makes in a given distance. But this methd remains very inaccurate fr several reasns. 2.1 What drives perfrmance Bus fleet run several rutes that are nt at all identical t ne anther, nr t a specific duty cycle. In fact, traffic and weather cnditins may well yield different duty cycles n the same rute, with the same driver perating the same bus. And duty cycle explains nly a prtin f the verall bus perfrmance. The fllwing characteristics als cntribute : TABLE 1 Determinants f Perfrmance Vehicle speed Engine Speed Actual Engine Per Trque Engine Demand - Percent Trque Drivers Behaviur: Demand (Percent Trque) Breaking Bus lading (number f passengers) Envirnmental cnditins temperature rad cnditins wind speed and directin traffic density Hwever, characterising a duty cycle, indeed a number f duty cycles within a given fleet, has been very expensive t date. Fr several decades, diesel buses were the nly ptin n the market (CNG buses had their chance when the successive energy crisis hit Nrth America in the 70 s and 80 s, but failed miserably n accunt f their lack f reliability). Given the small difference in perfrmance ffered by the bus manufacturers equipping their vehicles with the same (r very similar) engines, life cycle cst calculatins and technlgy cmparisns were superfluus. But the game has changed. 2.2 Technlgies and chices It is ne thing t cmpare ne diesel bus mdel t tw thers, but it is much mre cmplicated t lk at the fllwing range f technlgies available t urban fleet managers: TABLE 2 Urban Bus Technlgies Prpulsin type: Hybrid electric (partially electric bus where, the mtr is electric, but the n-bard energy surce is nt): Hybrid electric-petrleum buses (such as diesel-electric buses, the mst cmmercially ppular) Hybrid electric- natural gas buses (where the ICE is pwered by either CNG r LNG) Hybrid electric- mechanical buses (with a mechanical device [pneumatic, flywheel. ] acting as a secnd surce f pwer) Hybrid electric (tw surces f electric pwer) buses (such as fuel-cell / battery r fuel-cell/ultracap/supercap buses) Trlleybuses (where the surce f pwer is nt, fr the mst part, n bard the bus) All electric buses (that have a single surce f electric pwer such as batteries r fuel cell) Pwertrain cnfiguratins: There are tw main types f hybrid buses, series and parallel cnfiguratin, with several variatins: Parallel hybrid Mild parallel hybrid Pwer-split r series-parallel hybrid Series hybrid Plug-in hybrid electric bus Fuel cell, electric hybrid Electric buses use varius means t recharge their n-bard pwer supply: Cnductin charge at the dept (plug-in); Inductin charge when parked r at bus stps during service; Rapid cnductin charge at bus stps during service; Exchange f batteries when parked; Hydrgen refuelling at dept. As can be easily inferred, ne can n lnger cmpare purchase prices and a few ptins (such EVS27 Internatinal Battery, Hybrid and Fuel Cell Electric Vehicle Sympsium 2

3 as adding air cnditining r nt) t distinguish frm ne ffer t the next; such task has becme much mre cmplicated and fleet managers are generally ill-equipped fr the jb. In additin t cmparing vehicles, the imprtant and cstly mdificatins ften required t the infrastructures and practices f the rganisatin are n lnger mere incidentals. They include: TABLE 3 Impact f Bus Technlgy Chices n ther Organizatinal Cmpnents Infrastructures: Maintenance: Ceiling heights Safety equipment (air sensrs an fire fighting, fr example) Lift capacity Washers Refueling: Strage Cmpressin (gas) Liquefactin Gasificatin Safety Battery rm Pwer supply Battery chargers Rad Overpass Stps Wiring Pwer supply Energy banks (inductin) Training and skill sets mix: Drivers Mechanics Electricians Fire fighters and first respnders Others infrastructure / equipment: Bus barns r ther vernight facilities Tls On-rad repair / recvery Practices: Planning and scheduling Bus rtatins Number f busses required 3 The Slutin There is little dubt in anyne s mind that fleet truly dedicated t ptimizing their peratins and minimizing their carbn ftprint require a mre hlistic apprach than the ne used in the past. Lifecycle Cst Analysis and Emissin Calculatins are the mst advanced and helpful tls in ur arsenal t help fleet managers make the best pssible chices. But even these tls cannt prvide much help withut the accurate infrmatin that can nly be prvided by fully characterising the duty cycles at wrk in the system. 3.1 STEP 1: Prcuring Accurate Data Up t very recently, prcuring accurate data was time cnsuming, relatively cmplicated in terms f the quantity and type f equipment required nbard vehicles and therefre cstly. GSM Mdem Data Lgger Figure 1: Typical Data Cllectin Installatin n-bard a city bus New data lgging technlgy develped by FleetCarma greatly simplifies the installatin and reduces the cst f cllecting accurate data. A simple mdule is plugged int any vehicle s available OBD-II / J1939 prt with (r withut) the use f an adaptr and relays key infrmatin abut the vehicle via cellular netwrk. Furthermre, this infrmatin can be synchrnized with the the gelcatin f the vehicle in real time while it perfrms its standard duty. While a little mre EVS27 Internatinal Battery, Hybrid and Fuel Cell Electric Vehicle Sympsium 3

4 expensive than the base installatin (withut mdem and GPS), the full installatin saves the maintenance crew the time required t unplug and uplad the infrmatin n a daily r weekly basis. Cmpact data lgger clips in OBD-II prt J1939 Adapter Mdem mnitrs vehicle lcatin (GPS) and uplads data thrugh cell netwrk Figure 2: Data Cllectin Hardware, FleetCarma CrssChasm s FleetCarma data lgger clips int the standard prt available nbard mst buses t measure fuel usage & track vehicle lcatin. Custm J1939 adapters are als available t ensure the lggers are cnsistent with all heavyduty vehicles mdels, including plug-in electrics and hybrids. Data can be autmatically (and wirelessly) upladed t FleetCarma s database. In additin t prving accurate input t the lifecycle cst analysis prcess, FleetCarma brings cnsiderable added benefit thrugh a web prtal viewable by anyne in client rganizatin with prper lgin credentials. This web prtal supplies infrmatin regarding the fllwing real-wrld analytics: Distance traveled MPG Fuel usage Driving behaviur Idle statistics Utilizatin data Tailpipe and upstream emissins Figure 3: FleetCarma Analytics n its Web Prtal. This bjective trip statistics f duratin, distance traveled and fuel usage are dwnladable and exprtable in Excel and PDF frmats. GPS data analysis n vehicle lcatin is als available and prvides an assessment f which vehicles & rutes wuld be gd fits fr specific prpulsin systems, f fleet-wide charging / refueling pints. The data is exprtable t Ggle maps fr ease f visualizatin. This vehicle passes thrugh the radius f an electric charging statin X number f times a day in the curse f its regular rute Figure 4: Sample utput frm Web Prtal. EVS27 Internatinal Battery, Hybrid and Fuel Cell Electric Vehicle Sympsium 4

5 Once the challenge f characterising duty cycles fr an urban transit system (r any ther grund transprtatin fleet) has been vercme, it is pssible t rely n a mre empirical methd f prpulsin technlgy selectin. 3.2 STEP 2: Frecasting Fuel Cnsumptin In rder t predict fuel usage in a reliable way, it is necessary t build and validate predictive mdels fr the whle range f duty cycles experienced by the target fleet. Such mdels simulate fuel cnsumptin fr alternative prpulsin vehicles (CNG / Diesel Hybrid / Electric) t quantify ptential savings by rute and calculatins acrss the entire fleet. The pilt prject cnducted at the Trnt Transit Cmmissin (TTC), the largest urban transit fleet in Canada, illustrates ur methds best. It is imprtant t pint ut that this ptimisatin prject did nt invlve the recnfiguratin f the rutes designed by TTC planners. It simply assumed that such rutes had already been ptimized fr service delivery purpses. Fr the purpses f this prject, GPS results were used t identify which rute was being repeated fr each day. In ur rute samples, Diesel-Electric Hybrid Buses cnsumptin ranged frm 43 t 62 L/100km f diesel fuel n different rutes. Figure 6: TTC Fuel Cnsumptin Data. An analytical mdel was develped t enable fleet peratrs t estimate fuel cnsumptin based upn drive cycle characteristics. This analytical mdel apprach was then cmpared t a simulatin based apprach which was develped fr this prject. The analytical mdel apprach had n average ver 10% errr between the predicted fuel cnsumptin and the actual fuel cnsumptin fr a given rute. The simulatin based apprach n the ther hand had less than 3% errr n average. By expanding this high fidelity vehicle mdeling based apprach t different vehicle pwertrain cnfiguratins, CrssChasm was able t accurately predict hw different technlgies wuld perfrm n different real-life TTC rutes as well as hw they wuld perfrm n standard drive cycles. Figure 5: TTC Data fr Analysis. In selecting rutes, we ensured that Mst Urban, Average, and Least Urban rutes were captured, including stem_t and stem_frm cmpnents f the duty cycles fr cmprehensive analysis. Figure 7: High Fidelity Simulated Fuel Cnsumptin f Different Bus Pwertrain Types n Different Real-life TTC Rutes and sme Industry Standard Drive Cycles The results clearly demnstrate that different drive cycles have a substantial impact n a vehicle s fuel cnsumptin. EVS27 Internatinal Battery, Hybrid and Fuel Cell Electric Vehicle Sympsium 5

6 Figure 8: Fuel Savings f Hybrid Bus vs. Diesel Bus n Different "Real-Life" TTC Rutes and n "Industry Standard" Drive Cycles Switching t hybrid buses can yield immense fuel savings n certain rutes while they can be negligible n ther rutes. The mst imprtant lessn t be retained here is the imprtance f ding data acquisitin n the rutes f interest prir t making any predictive calculatins. Taking smene else s infrmatin and assuming that it applies t the case at hand is a recipe fr disaster. Nt using data gathered directly n the fleet under investigatin guarantees that fuel cnsumptin numbers will either be t lw r t high. This errr can ften cmpletely skew the results f an analysis. In the case f a large transit fleet, this can easily lead t bad decisins csting hundreds f millins f dllars mre than if prper data lgging and simulatins had been perfrmed prir t the decisin prcess. 3.3 STEP 3: Identifying ther csts Albeit imprtant, the cst f fuel is but ne cmpnent that must be cnsidered in the prcess f ptimizing a fleet. Newer technlgies (than the incumbent diesel bus) are ntriusly mre expensive t purchase and ften require ther changes with either psitive, r negative impact n the verall cst f running a fleet. These ther csts can be critical t the selectin f a bus prpulsin technlgy, and, at the very least, the fllwing items must be taken int cnsideratin: VEHICLE ACQUISITION COST Base price fr buses Warranty cnditins Share f price cvered by utside agency (may vary frm ne technlgy t the ther) INFRASTRUCTURE MODIFICATIONS Buildings Garage drs Washing facilities Rf clearance Battery rm (fr lead-acid batteries nly) Additinal spare parts space Safety / Leak detectin equipment Equipment Lifts Battery cnditiner Others (ex. battery handling) Statins and ther assets Transit way statins Bus stp shelters Private prperty cmpensatin Others OPERATING DATA Energy strage life expectancy (years) Fuel prices (current and frecasted) MAINTENANCE COSTS Energy Strage replacement (per bus) Nn-scheduled energy strage system replacement (per bus) Annual preventive maintenance (pwer pack) Energy Strage System dispsal csts (per bus) Pwer Inverter Mdule (PIM) Pwer train (Incl: turbcmpressr) Engine replacement Transmissin replacement Preventive maintenance (annual) Starter Frame, steering and suspensin (annual per bus) Annual brake maintenance (per bus) Others Other Transit System specific cst SPARE PARTS COSTS (Fleet) Additinal inventry required Annual carrying cst f inventry NON-RECURRING SOFT COSTS HPS Prject - feasibility study HPS Prject management Preventive maintenance - Reprgramming Training Maintenance emplyees Number f emplyees t train Applicable rate Time required (hurs) Drivers Number t train Applicable rate (in CAD) Time required (hurs) Others Number t train Applicable rate (in CAD) EVS27 Internatinal Battery, Hybrid and Fuel Cell Electric Vehicle Sympsium 6

7 Time required (hurs) Mdificatins t service plan Mdificatins t lng-term planning Tling (ex. Energy strage system servicing) Advertising & prmtin INDIRECT BENEFITS Increase in ridership (in %) Average fare Current ridership Resulting increase in revenues A full evaluatin f the impact f implementing new technlgies may require ther studies t be cnducted in rder t btain accurate input n these varius items. Fr example, depending n the state and age f existing facilities, it may be wise t cnsider building new nes, especially when it is peratinally difficult r cstly t accmmdate the cexistence f cnventinal diesel buses and newer technlgies (such as CNG r Hydrgen Fuel Cell) within the same maintenance garages while transiting t that new technlgy. 3.4 STEP 6: Using TLC BU$ The first ttal lifecycle cst estimating mdel develped by MARCON ( was used in the cntext f a benchmark prject that examined the pssibility f cnverting the Canadian urban transprtatin bus fleet t use hydrgen fuel cell pwer in electric buses 1. Later n, MARCON s assignments with several Canadian urban transprters such as the Sciété des transprts de Mntréal, OC Transp (Ottawa), and the Sciété de transprt de l Outauais (Gatineau) allwed us t perfect the mdel called Ttal Life Cycle Bus r TLC BU$. Further wrk perfrmed fr the Canadian Urban Transprtatin Assciatin lead t a simplified versin f the mdel (TLC BU$ Lite ) that culd be used (withut ur help) by subscribers in making a first, mre superficial evaluatin, withut incurring great csts. While duty cycle data used in such evaluatins can be prvided by third parties (independent labratries, bus manufacturers, etc.), fleet managers are reminded that the accuracy f the cnclusins is always dependant n the accuracy f the input prvided by such third parties. We therefre highly recmmend the use f the FleetCarma data cllectin and analysis services ( as a first step in the evaluatin prcess. The CrssChasm Technlgies team has a prven track recrd, a cmbined 30 years f expertise and 11 industry awards. FleetCarma characterizes each rute in a fleet inexpensively, accurately, reliably and rapidly, taking the apprximatin ut f the lifecycle cst evaluatin prcess. 4 Sample results In the capital f Canada, Ottawa, TLC BU$ was used t cmpare several alternate prpulsin ptins fr the purchase f 226 buses (12 m.). The value f such an acquisitin ranged frm 90M$ t 140M$ fr the vehicles alne. Althugh bi-diesel, hydrgen fuel cell and hythane buses were cnsidered, we will use nly the results fr cnventinal diesel, cmpressed natural gas (CNG) and diesel-electric hybrid (DEH) buses in this presentatin. Capital investment csts are the easiest t determine, assuming the infrmatin is accessible fr infrastructure cmpnents. In additin t the cst f the vehicles, mdificatins and additins t the peratr s maintenance and garaging facilities are required in sme cases (drs, gas detectrs, ventilatin systems, battery recycling rm, etc.). In this case, rad installatins (bus stp shelters, verpasses, ) als required changes, as DEH and CNG buses tend t be higher than cnventinal diesel buses. Table 2: Capital Investment Csts at OC Transp DIESEL CNG DEH Capital Investment Csts Bus acquisitin Building and Infrastructure cst Other sft, nnrecurring csts Ttal capital csts: Fuel csts are nt s easily determined. Buses in Canadian urban transit systems remain in service fr an 18-year perid. In additin t fuel cnsumptin, the price f varius energy surces must be frecasted fr almst tw decades. While the price f electricity is fairly stable in Canada and 10-year cntracts can be signed fr natural gas supply, the price f diesel fuel fr such a lng perid is difficult t pin dwn and ne must rely f institutins such as the Internatinal Energy Agency whse track recrd in such matters is n better and n wrse than anyne else. As a result f the calculatins perfrmed at a time that predates the crash f natural gas prices in Nrth America, the fuel csts fr each ptin ver the 18 year lifetime f the 226 buses were: EVS27 Internatinal Battery, Hybrid and Fuel Cell Electric Vehicle Sympsium 7

8 Table 3: Frecasted Fuel Csts at OC Transp Diesel (fleet average) $161.2M Diesel (lw speed/high stp) $223.8M CNG (general allcatin) $112.1M DEH (lw speed/high stp allcatin) $163.4M This data demnstrates clearly that if DEH buses are nt allcated t rutes where they can perfrm in an ptimal manner, they will nt save their wner anything and may, in cases even cst mre in fuel than their cnventinal cunterparts. The TTC, fr example, experienced nly 5% reductin in fuel cst with their DEH buses fleet because they d nt make prper allcatin f this technlgy n their rutes, claiming unin cntract cnstraints t act in such manner. At tday s market price fr natural gas, the advantage f CNG buses wuld clearly imprve. Figure 6: NG histrical cmmercial prices in NA (in USD per thusand cubic feet) When ther perating csts were added t the analysis and all csts were discunted the net present value, the final tally yielded tw sets f results based n bus allcatins Jan Oct Jul Apr Jan Oct Jul Apr Jan Oct Table 4: Lifecycle csts at OC Transp Average Fleet Allcatin DIESEL CNG Capital Investment Csts Bus acquisitin 90,108,581 95,366,244 Building and infrastructure cst 0 50,207,748 Other sft, nn-recurring csts 0 692,074 Ttal capital csts: 90,108, ,266,066 Operating Csts O&M cst (excluding fuel) 192,698, ,902,965 Fuel cst 161,193, ,051,396 Electricity (cmpressr) 0 6,293,399 Ttal perating csts: 353,892, ,247,760 Nn-Discunted Ttal Cst 444,000, ,513,826 Discunted Ttal Cst 302,108, ,267,256 Jul Apr Jan Oct Jul Apr Jan Oct Table 5 : Lifecycle csts at OC Transp Lw Speed / Frequent Stps DIESEL DEH Capital Investment Csts Bus acquisitin 90,108, ,816,714 Building and infrastructure cst 0 1,763,264 Other sft, nn-recurring csts 0 955,283 Ttal capital csts: 90,108, ,535,262 Operating Csts O&M cst (excluding fuel) 246,834, ,890,809 Fuel cst 223,774, ,361,122 Battery replacement cst 0 25,481,952 Other csts 0 5,078,268 Ttal perating csts: 470,609, ,812,151 Nn discunted Ttal Cst 560,718, ,347,413 Discunted Ttal Cst 373,459, ,250,148 Fleet peratrs made this bus allcatin decisin (DEH buses n ptimal rutes and CNG buses n average rutes) because they were nt prepared t mdify their current prcedures fr CNG buses where they wuld fr DEH buses. In mst fleet, new busses are allcated first t high stps/lw speed rutes and, as they aged, allcated t less strenuus duty cycles. 5 Learnings and Cnclusins Over and abve lifecycle csts, a full analysis must take the fllwing int cnsideratin: Technical perfrmance f prpulsin technlgy t date Envirnmental perfrmance Transit system s histry with varius technlgies Climatic cnditins In shrt, accrding t ur experience cmparing varius technlgies in the field and cnsidering all the (ratinal) factrs fleet managers must deal with, energy efficiency f varius ptins alne des nt justify the adptin f an alternate bus prpulsin technlgy. A much brader analysis must be cnducted t determine where electric and hybrid electric buses perfrm best. Generally speaking, and frm an energy efficiency standpint alne, electric hybrid vehicles perfrm best n rutes with mre stps per kilmetre and lwer average speed. That being said, n pragmatic technlgy purchase decisin by a transit fleet shuld be dne withut first establishing the drive cycles f the feet s current and prjected rutes and then perfrming validated fuel cnsumptin simulatins n thse exact rute drive cycles fr different pwertrain technlgies. EVS27 Internatinal Battery, Hybrid and Fuel Cell Electric Vehicle Sympsium 8

9 Average)Speed) LNG)/)CNG) Buses) ) ) Cnven&nal)) Diesel)Buses) ) ) Electric) Hybrid)Eletric) Buses) Stps/km) Figure 9: Optimal Range fr three bus prpulsin technlgies. While results based n average speed and stps/km tend t favr different technlgies based n the graph in Figure 9, MARCON and CrssChasm believe it shuld be mandatry fr transit fleets wh are subsidized by public funds t perfrm a thrugh investigatin f where hw different vehicle technlgies will perfrm n their rutes, prir t new purchases implementing. Past prjects have demnstrated that the cst f such a pragmatic apprach is usually rders f magnitude smaller than the cst f nt making the ptimal decisin. In fact, each technlgy perfrms best under a certain set f circumstances that include many mre factrs discussed earlier than this simple representatin. Only in fleet data acquisitin can truly capture the circumstances affecting a given rute. Each bus prpulsin system can nevertheless cntribute t ptimizing the fleet by imprving its energy efficiency and minimizing its verall csts. The 360-degree analysis perfrmed n behalf f several clients and the business case used in this article demnstrate the relevance f electric bus technlgies in the prtfli f vehicles that cmprise a transit fleet as lng as there is a sufficient number f vehicles in such a fleet t justify the investments required in adapting the facilities t their use. Acknwledgments The authrs wuld like t acknwledge their numerus clients fr giving them the pprtunity t develp their skills and knwledge. References [1] Pierre Ducharme and MARCON, Transfrming the future: Mving Tward Fuel Cell-Pwered Fleets In Canadian Urban Transit Systems, NRCan Publicatin, M38-24/ and [2] Matthew Stevens, Jen Bauman, Chris Mendes CrssChasm Tech and Ray Minat, Larry Zhu Inertia Engineering, Maximizing the benefit f hybrid buses, Reprt t the Trnt Transit Cmmissin, [3] Matthew Stevens & Simn Ouellette, Hybrid Buses: Real-Wrld meets Simulatins, EMC Publicatin f EV2010 & 2011 Prceedings, [4] Pierre Ducharme and William Bugyra, CNG Bus Optin Evaluatin fr the City f Ottawa, Reprt t OC Transp, Authrs Pierre Ducharme is the president and c-funder f MARCON Management Cnsultants Inc., a cnsulting firm specialising in transprtatin and energy. Pierre is the main architect f TLC BU$, the ttal lifecycle cst evaluatin mdel described in this presentatin. Pierre studied at the Ryal Military Cllege f Canada in Quantitative Methds f Management, at Université du Québec in Mntréal (in Business Administratin and at McGill University where he btained his D. Mgt. Pierre prvides advice t fleet managers regarding ptimal fleet cnfiguratins as well as strategic advice t gvernment in energy efficiency prgram design. He is the authr f Canada s secnd largest prvince s Public Transprtatin Electrificatin Strategy (2012). EVS27 Internatinal Battery, Hybrid and Fuel Cell Electric Vehicle Sympsium 9