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Ford's thermal management with batteries. Presenter Robert Taenaka, Ford Motor Co.

The Focus Electric is Ford�s first full-featured 5 passenger battery electric vehicle. The engineering team set our sights on achieving best-in-class function and efficiency and was successful with an EPA certified 1XX MPGe and range XXX then the facing competition allowing for a slightly lower capacity battery pack and larger vehicle without customer trade-off. We briefly overview the engineering method and technologies employed to deliver the results as well as sharing some of the functional challenges unique to this type of vehicle. Presenter Charles Gray, Ford Motor Co.

The presentation offers a brief history of the electric vehicle and parallels the realities of those early vehicles with the challenges and solutions of the electrified vehicles coming to market today. A technology evolution for every major component of these vehicles has now made this mode of transportation viable. The Focus Electric is Ford's first electric passenger car utilizing the advanced technology developments to meet the needs of electric car buyers in this emerging market. Presenter Charles Gray, Ford Motor Co.

Plug In Charging Systems are mainly responsible for transferring energy from the electric power grid into one or more vehicle energy storage devices (e.g. batteries). A satisfactorily operating Plug in Charging System has the following three key performance characteristics. First, the charge process starts up easily. Second, it completes the charge process within some expected time. Third, it charges efficiently so that excessive amounts of power are not wasted. When a Plug In Charging System malfunction exists and negatively affects one or more of these key performance criteria, it is the responsibility of the OBD monitoring system to identify the fault and notify the customer. The presentation will discuss the key performance characteristics described above and some of the diagnostic strategies used to detect faults. The discussion will also include an overview of MIL illumination and freeze frame storage capabilities.

In this paper a diagnostic design process is proposed for developmental vehicles where mainstream design process is not well-suited. First a review of current practice in on-board vehicle fault diagnostics design is presented with particular focus on the application of this process to the development of the Ford Escape Hybrid Electric Vehicle (HEV) program and a demonstration Fuel Cell Electric Vehicle (FCEV) program. Based on the review and evaluation of these experiences, a new tool for diagnostics design is proposed that promises to make the design more traceable, to reduce the repetition of work, and to improve understandability and reuse.

When a vehicle with a partially filled fuel tank undergoes sudden acceleration, braking, turning or pitching motion, fuel sloshing is experienced. It is important to establish a CAE methodology to accurately predict slosh phenomenon. Fuel slosh can lead to many failure modes such as noise, erroneous fuel indication, irregular fuel supply at low fuel level and durability issues caused by high impact forces on tank surface and internal parts. This paper summarizes activities carried out by the fuel system team at Ford Motor Company to develop and validate such CAE methodology. In particular two methods are discussed here. The first method is Volume Of Fluid (VOF) based incompressible multiphase Eulerian transient CAE method. The CFD solvers used here are Star CD and Star CCM+. The second method incorporates Fluid-Structure interaction (FSI) using Arbitrary Lagrangian-Eulerian (ALE) formulation.

Pareto optimal map concept has been applied to the optimization of the vehicle system control (VSC) strategy for a power-split hybrid electric vehicle (HEV) system. The methodology relies on an inner-loop optimization process to define Pareto maps of the best engine and electric motor/generator operating points given wheel power demand, vehicle speed, and battery power. Selected levels of model fidelity, from simple to very detailed, can be used to generate the Pareto maps. Optimal control is achieved by applying Pontryagin's minimum principle which is based on minimization of the Hamiltonian comprised of the rate of fuel consumption and a co-state variable multiplied by the rate of change of battery SOC. The approach delivers optimal control for lowest fuel consumption over a drive cycle while accounting for all critical vehicle operating constraints, e.g. battery charge balance and power limits, and engine speed and torque limits.

The compressive behavior of lithium-iron phosphate battery cells is investigated by conducting in-plane constrained compression tests and out-of-plane compression tests of representative volume element (RVE) specimens. The results for cell RVE specimens under in-plane constrained compression tests without pre-strains and with pre-strains in the out-of-plane direction indicate that the load carrying capacity is characterized by the buckling of cell specimens. As the pre-strain increases, the nominal compressive stress-strain curve becomes higher. The nominal stress-strain curves in the out-of-plane direction were also obtained and used to determine the elastic moduli for the elastic buckling analyses of the cell components in the cell RVE specimens with different pre-strains. Based on the elastic buckling analyses for a beam with different lateral constraints due to different pre-strains in the out-of-plane direction, the number of half waves and the buckling stresses were obtained.

In vehicle design, response surface model (RSM) is commonly used as a surrogate of the high fidelity Finite Element (FE) model to reduce the computational time and improve the efficiency of design process. However, RSM introduces additional sources of uncertainty, such as model bias, which largely affect the reliability and robustness of the prediction results. The bias of RSM need to be addressed before the model is ready for extrapolation and design optimization. This paper further investigates the Bayesian inference based model extrapolation method which is previously proposed by the authors, and provides a systematic and integrated stochastic bias corrected model extrapolation and robustness design process under uncertainty. A real world vehicle design example is used to demonstrate the validity of the proposed method.

Electric vehicles are receiving considerable attention because they offer a more efficient and sustainable transportation alternative compared to conventional fossil-fuel powered vehicles. Since the battery pack represents the primary energy storage component in an electric vehicle powertrain, it requires accurate monitoring and control. In order to effectively estimate the battery pack critical parameters such as the battery state of charge (SOC), state of health (SOH), and remaining capacity, a high-fidelity battery model is needed as part of a robust SOC estimation strategy. As the battery degrades, model parameters significantly change, and this model needs to account for all operating conditions throughout the battery's lifespan. For effective battery management system design, it is critical that the physical model adapts to parameter changes due to aging.

Designing a vehicle body involves meeting numerous performance requirements related to different attributes such as NVH, Durability, Safety, and others. Multi-Disciplinary Optimization (MDO) is an efficient way to develop a design that optimizes vehicle performance while minimizing the weight. Since a body design evolves in course of the product development cycle, it is essential to repeat the MDO process several times as a design matures and more accurate data become available. This paper presents a real life application of the MDO process to reduce weight while optimizing performance over the design cycle of the 2015 Mustang. The paper discusses the timing and results of the applied Multi-Disciplinary Optimization process. The attributes considered during optimization include Safety, Durability and Body NVH. Several iterations of MDO have been performed at different milestones in the design cycle leading to a significant weight reduction of the already optimized design by over 16kg.

Torque controls for the engine and electric motors in a Powersplit HEV are keys to the success of balancing fuel economy, driveability, and battery power control. The electric variable transmission (EVT) offers an opportunity to let the engine operate at system-optimal fuel efficient points independently of any load. Existing work shows such a benefit can be realized through a decentralized control structure that translates the driver inputs to independent engine torque and speed control. However, our study shows that the decentralized control structures have a fundamental limitation that arises from the nonminimum phase (NMP) zero in the transfer function from the driver power command to the generator torque change rate, and thus not only is it difficult to obtain smooth generator torque but also it can cause violations on battery power limits during transients. Additionally, it adversely affects the driveability due to the generator torque transients reflected at the ring gear.

As automakers strategize approaches to sustainable vehicle technologies, alternative powertrains must be considered to reduce future fleet vehicle emissions and improve energy security. These alternative vehicles include different fuels and electrification. The ultimate for on-road CO2 reductions is a zero emission vehicle, which can be achieved by either a hydrogen fuel cell or battery electric vehicle. These vehicles would also require a renewable energy source to provide their propulsion energy in order to achieve maximum sustainability for both CO2 reduction and energy security. Renewable energy sources such as wind or solar result in heat or electricity that needs to be generated into an energy carrier such as hydrogen or stored in a battery. When examining these options based strictly on the efficiency path, previous analysis have concluded fuel cell vehicles may not be an appropriate suitability strategy in comparison to battery electric vehicles.

A life-cycle assessment (LCA) has been developed to help compare the economic, environmental and energy (EEE) impacts of converting coal to automotive fuels in China. This model was used to evaluate the total economic cost to the customer, the effect on the local and global environments, and the energy efficiencies for each fuel option. It provides a total accounting for each step in the life cycle process including the mining and transportation of coal, the conversion of coal to fuel, fuel distribution, all materials and manufacturing processes used to produce a vehicle, and vehicle operation over the life of the vehicle. The seven fuel scenarios evaluated in this study include methanol from coal, byproduct methanol from coal, methanol from methane, methanol from coke oven gas, gasoline from coal, electricity from coal, and petroleum to gasoline and diesel. The LCA results for all fuels were compared to gasoline as a baseline case.

There are a number of benefits from Ford Motor Company's participation in motorsports. This paper will describe how an engineering team developed a CAE process to assist in the design of a race car to meet impact requirements, with the technology transfer benefit of improved impact performance of composite structures in passenger cars. In 1997/98, a CAE process was developed and applied in the design and test of Formula One race car composite impact structures. For this particular engineering effort, a Ford proprietary software program, COMP-COLLAPSE, was the primary analysis tool that was utilized to successfully predict impact performance. As a result, COMP-COLLAPSE was used extensively in the design of race car composite impact structures. There were two beneficiaries from this effort: Race Vehicles: Improved vehicle impact performance as well as design improvement in crush efficiency, packaging, weight, and manufacturing.

This paper is the first in a series of documents designed to record the progress of the SAE J2293 Task Force as it continues to develop and refine the communication requirements between Plug-In Electric Vehicles (PEV) and the Electric Utility Grid. In February, 2008 the SAE Task Force was formed and it started by reviewing the existing SAE J2293 standard, which was originally developed by the Electric Vehicle (EV) Charging Controls Task Force in the 1990s. This legacy standard identified the communication requirements between the Electric Vehicle (EV) and the EV Supply Equipment (EVSE), including off-board charging systems necessary to transfer DC energy to the vehicle. It was apparent at the first Task Force meeting that the communications requirements between the PEV and utility grid being proposed by industry stakeholders were vastly different in the type of communications and messaging documented in the original standard.

The Auto Industry is responding to the environment and energy conservation concerns by ramping up production of hybrid electric vehicles (HEV). As the initial hurdles of making the powertrain operate are overcome, challenges such as making the powertrain feel more refined and intuitive remain. This paper investigates one of the key parameters for delivering that refinement: engine RPM behavior. Ideal RPM behavior is explored and included in the design of a control system. System implications are examined with regard to the effect of engine RPM scheduling on Battery usage and vehicle responsiveness.

The SAE Fuel Cell Vehicle (FCV) Safety Working Group has been addressing FCV safety for over 10 years. The initial document, SAE J2578, was published in 2002. SAE J2578 has been valuable as a Recommended Practice for FCV development with regard to the identification of hazards associated with the integration of hydrogen and electrical systems onto the vehicle and the definition of countermeasures to mitigate these hazards such that FCVs can be operated in the same manner as conventional gasoline internal combustion engine (ICE)-powered vehicles. An update to SAE J1766 for post-crash electrical safety was also published in 2008 to reflect unique aspects of FCVs and to harmonize electrical requirements with international standards. In addition to SAE J2578 and J1766, the SAE FCV Safety Working Group also developed a Technical Information Report (TIR) for vehicular hydrogen systems (SAE J2579).

As automotive manufacturers continue to increase their use of thermoplastics for interior and exterior components, there is a likelihood of squeaks due to material contacts. To address this issue, Ford's Body Chassis NVH Squeak and Rattle Prevention Engineering Department has developed a tester that can measure friction, and any accompanying audible sound, as a function of sliding velocity, normal load, surface roughness, and environmental factors. The Ford team has been using the tester to address manufacturing plant issues and to develop a database of polymeric material pairings that will be used as a guide for current and future designs to eliminate potential noise concerns. Based upon the database, along with a physical property analysis of the various plastic (viscoelastic) materials used in the interior, we are in the process of developing an analytical model which will be a tool to predict frictional behavior.

While a Ni-MH battery has good performance properties, such as a high power density and no memory effect, it needs a powerful thermal management system to maintain within the required narrow thermal operating range for the 42V HEV applications. Inappropriate battery temperatures result in degradation of the battery performance and life. For the battery cooling system, air is blown into the battery pack. The exhaust is then vented outside due to potential safety issues with battery emissions. This cooling strategy can significantly impact fuel economy and cabin climate control. This is particularly true when the battery is experiencing frequent charge and discharge of high-depths in extreme hot or cold weather conditions. To optimize performance and life of HEV traction batteries, the battery cooling design must keep the battery operation temperature below a maximum value and uniform across the battery cells.