Enhanced Plug-in Hybrid Electric Vehicles Alan Millner, Nicholas Judson, Bobby Ren, Ellen Johnson, William Ross Massachusetts Institute of Technology Lincoln Laboratory. 244 Wood St. Lexington, MA 02420 {amillner, judson, bobby.ren, ejohnson, bross}@ll.mit.edu Abstract—Plug-in hybrid electric vehicles (PHEVs) have By shifting our least efficient energy conversion step from the potential to reduce fossil fuel use, decrease pollution, inefficient small engines to central power plants, the total and allow renewable energy sources for transportation, but well to wheel efficiency of our transportation sector can be their lithium ion battery subsystems are presently too greatly improved. Also, use of electric power transmission expensive. Three enhancements to PHEVs are proposed and distribution allows the source of transport energy to be here that can improve the economics. First, the renewable sources, nuclear, or natural gas, with far greater incorporation of location information into the car’s energy long term supplies and lower carbon footprint. If half the management algorithm allows predictive control to reduce passenger vehicle fleet of the US were replaced by 100 mile fuel consumption through prior knowledge of the upcoming per gallon (mpg) plug-in hybrids, the petroleum use of the route and energy required. Second, the use of the vehicle US would be reduced by approximately the amount now battery while parked, offsetting the short peaks in imported from the Mideast. Our CO2 emissions would be commercial-scale facility electrical demand to reduce reduced by 0.5 billion tons per year, or 8%. Use of plug-in demand charges, can provide additional revenue to pay for hybrid electric vehicles (PHEVs) allows the limited use of the battery. Third, the battery cycle life must be maximized liquid fuels to extend range when that is needed for to avoid high replacement costs; a model of battery wear convenience, taking advantage of their very high energy out for lithium ion batteries is presented and is used to density, while addressing the need for fuel conservation confirm that the above strategies are compatible with long during the typical shorter commuting trips that dominate battery life. usage. PHEVs are becoming available. Conversions such as the 1. BACKGROUND: A VISION FOR PHEVS A123 Systems, Inc. Hymotion L5 converted Toyota Prius hybrid have been sold in quantities of hundreds for several years now. The General Motors Chevrolet Volt is due late The US energy economy suffers from the use of too much this year, and the Toyota Prius PHEV is scheduled for petroleum. This is a problem because the world’s oil release in 2011. Other sources are under development, reserves are in places far from our national borders and including some suitable for trucks and military vehicles. often governed by countries with different political agendas; 60% of the reserves are in the Mideast [1]. It is also a The problem holding back this technology now is the high problem because the long term supply of petroleum is cost of the battery subsystem. Lithium ion batteries, the limited, with discoveries declining since 1964 [2]. And, it is technology of choice today, are expensive and will probably a problem because our burning of this non-renewable remain so for some years to come. For example, the resource produces too much greenhouse gas, with 25% of aforementioned Toyota Prius conversion by A123 Systems CO production coming from the US, and 33% of US CO 2 2 in 2008 cost about $32,000: $22,000 for the hybrid car, and coming from oil. Transportation represents 28% of US $10,000 for the retrofit module with a 5 kWh battery pack. energy use and 70% of petroleum use [1]. Vehicles at this cost level can be leased for approximately $400 per month. The larger the battery capacity, the more Power obtained from gasoline burned in automobile engines expensive the PHEV becomes. is extremely inefficient, with an average final efficiency of only 15%, with the rest wasted in heat and drive train losses The solution envisioned here is to first make use of an [3]. By comparison, central electric power plants operate at efficient vehicle with the battery sized to address common an efficiency of 35% [1]. commuting distances electrically. Then, make best use of intelligent controls to minimize fuel consumption by ___ making predictive use of knowledge of the route to be This work was sponsored by the United States Government traveled. Third, use the battery to provide grid regulation under Air Force contract FA8721-05-C-0002. Opinions, services through peak power shaving while parked at work, interpretations, conclusions, and recommendations are those a version of vehicle to grid (V2G) power transfer that makes of the authors and not necessarily endorsed by the United use of the economic relationship between a commuter and States Government. employer and that we call vehicle to building (V2B), generating revenue to offset the battery cost. And finally, make use of good battery life models to minimize degradation of the battery while it is used for both Gas Gas Trans- transportation and regulation. By enhancing the PHEV in Shaft Road these ways, the high initial cost of battery subsystems can Tank Engine mission be addressed and moderated. By allowing economies of Friction Electric scale to be reached through the manufacture of the large Generator Acceleration production quantities of PHEVs, this may bootstrap the Motor Elevation technology into a viable production range. Wind Inverter Charger 2. PREDICTIVE CONTROL OF VEHICLE ENERGY Battery The concept of improving fuel economy by foreknowledge of the route to be traveled, using global positioning satellite V2B (GPS) and other available sources of information, has been V2G considered for some years now [4, 5]. The creation of Utility Charger simple control algorithms making use of specific information for a parallel or series-parallel hybrid vehicle Figure 1. Vehicle energy model; each boxed element has an has not been clear. Presented here is an approach that makes efficiency dependent on energy flow through that element. use of at least the distance to be traveled, and potentially the Energy flow directions are indicated by arrows and external elevation changes to be encountered, speed changes sources of energy and driving conditions that affect energy including expected traffic congestion, road surfaces, and expenditure are indicated. other factors affecting dynamic vehicle power demand, to predict the requirements on the vehicle power plant over its A simple power flow model of a PHEV vehicle was created trip, and schedule the use of electrical or liquid fuel energy using MATLAB [7] with vehicle weight, rolling resistance, to optimize engine efficiency and minimize fuel use. and aerodynamic parameters modeled on the 2010 Toyota Prius. This included a model of each major component The present state of the art is to operate a PHEV with as (Figure 1), with energy efficiency as a function of power much energy as possible coming from the battery until it level through that component. A state diagram control reaches a low state of charge [6]. Then energy is obtained strategy was implemented for this vehicle diagram (Figure from the liquid fuel engine to sustain this minimum battery 2), in which the state variables are the power required of the charge for the rest of the trip. The problem with this strategy system at that time and the state of charge (SOC) of the is that over that last part of the trip, the engine is often battery. required to operate at a power level that is not its optimum operating point. If more battery energy is saved until later in the trip, however, this optimization can be extended and fuel Full saved. Mech- anical Braking To test this concept, a model was needed of the vehicle, the Max Variable Electric Maximum Electric Max vehicle energy control system, and the driving cycle or route Only + Variable Gas Electric including speed vs. time. This allows evaluation of + predictive control strategies and comparison with Max Gas conventional strategies, to determine quantitative benefits in Target Optimum terms of improved fuel consumption. Regen Variable Electric Gas Charging + Optimum Gas Battery SOC Charging Min Variable Gas Only Maximum Gas Charging Only Empty Max Braking Zero Power Max Electric Max Electric Max Electric Gas Optimum + Max GasMax Demand + Gas Optimum Power Demand by Car Figure 2. Vehicle controller state machine; states are dependent on power demand and battery SOC. As part of this control strategy, there is a parameter representing the target SOC of the battery. If this is taken to 3. VEHICLE TO BUILDING be the minimum SOC, then this strategy reduces to the conventional one of charge depletion followed by charge sustaining mode [6]. However, if this parameter is allowed Electric power customers with high power demand service, to vary over the trip, gradually reducing and reaching the such as large commercial and institutional ones, in addition minimum only at the end of the trip, then a more flexible to charges per kWh as residential customers are accustomed strategy emerges. to, also pay demand charges for the maximum number of kilowatts drawn during the billing period. These demand A comparison of control strategies was done for the charges generally start for customers exceeding 100-500 kW modeled vehicle with a 5 kWh battery capacity (the same as of peak power demand, depending on the utility provider. the A123 Systems, Inc. Hymotion L5 PHEV conversion) Often these charges are then the largest portion of the bill. over a route made up of three US06 driving cycles [8], to For MIT Lincoln Laboratory in the Boston area, the demand make a 24 mile trip typical of the length of daily commute charge is most of the electric bill.