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Battery temperature variations have a strong effect on both battery aging and battery performance. Significant temperature variations will lead to different battery behaviors. This influences the performance of the Hybrid Electric Vehicle (HEV) energy management strategies. This paper investigates how variations in battery temperature will affect Lithium-ion battery aging and fuel economy of a HEV. The investigated energy management strategy used in this paper is the Equivalent Consumption Minimization Strategy (ECMS) which is a well-known energy management strategy for HEVs. The studied vehicle is a Honda Civic Hybrid and the studied battery, a BLS LiFePO4 3.2Volts 100Ah Electric Vehicle battery cell. Vehicle simulations were done with a validated vehicle model using multiple combinations of highway and city drive cycles. The battery temperature variation is studied with regards to outside air temperature.

Efficiency testing of hybrid-electric vehicles is challenging, because small run-to-run differences in pedal application can change when the engine fires or the when the friction brakes supplement regenerative braking, dramatically affecting fuel use or energy regeneration. Electronic accelerator control has existed for years, thanks to the popularity of throttle-by-wire (TBW). Electronic braking control is less mature, since most vehicles don’t use brake-by-wire (BBW). Computer braking control on a chassis dynamometer typically uses a mechanical actuator (which may suffer backlash or misalignment) or braking the dynamometer rather than the vehicle (which doesn’t yield regeneration). The growth of electrification and autonomy provides the means to implement electronic brake control. Electrified vehicles use BBW to control the split between friction and regenerative braking. Automated features, e.g. adaptive cruise control, require BBW to actuate the brakes without pedal input.

This paper considers optimal power management during the establishment of an expeditionary outpost using battery and vehicle assets for electrical generation. The first step in creating a new outpost is implementing the physical protection and barrier system. Afterwards, facilities that provide communications, fires, meals, and moral boosts are implemented that steadily increase the electrical load while dynamic events, such as patrols, can cause abrupt changes in the electrical load profile. Being able to create a fully functioning outpost within 72 hours is a typical objective where the electrical power generation starts with batteries, transitions to gasoline generators and is eventually replaced by diesel generators as the outpost matures. Vehicles with power export capability are an attractive supplement to this electrical power evolution since they are usually on site, would reduce the amount of material for outpost creation, and provide a modular approach to outpost build-up.

This paper investigates an optimal design of a diesel engine and after-treatment systems for a series hybrid electric forklift application. A holistic modeling approach is developed in GT-Suite® to establish a model-based hardware definition for a diesel engine and an after-treatment system to accurately predict engine performance and emissions. The used engine model is validated with the experimental data. The engine design parameters including compression ratio, boost level, air-fuel ratio (AFR), injection timing, and injection pressure are optimized at a single operating point for the series hybrid electric vehicle, together with the performance of the after-treatment components. The engine and after-treatment models are then coupled with a series hybrid electric powertrain to evaluate the performance of the forklift in the standard VDI 2198 drive cycle.

Improving vehicle response through advanced knowledge of traffic behavior can lead to large improvements in energy consumption for the single isolated vehicle. This energy savings across multiple vehicles can even be larger if they travel together as a cohort in harmonization. Additionally, if the vehicles have enough information about their immediate path of travel, and other vehicles’ in that path (and their respective critical forward-looking information), they can safely drive close enough to each other to share aerodynamic load. These energy savings can be upwards of multiple percentage points, and are dependent on several criteria. This analysis looks at criteria that contributes to energy savings for a cohort of vehicles in synchronous motion, as well as describes a study that allows for better understanding of the potential benefits of different types of cohorted vehicles in different platoon arrangements.

This paper studies the hardware-in-the-loop (HiL) design of a power-split hybrid electric vehicle (HEV) for the research of HEV lithiumion battery aging. In this paper, an electrochemical model of a lithium-ion battery pack with the characteristics of battery aging is built and integrated into the vehicle model of Autonomie® software from Argonne National Laboratory. The vehicle model, together with the electrochemical battery model, is designed to run in a dSPACE real-time simulator while the powertrain power distribution is managed by a dSPACE MicroAutoBoxII hardware controller. The control interface is designed using dSPACE ControlDesk to monitor the real-time simulation results. The HiL simulation results with the performance of vehicle dynamics and the thermal aging of the battery are presented and analyzed.

A Dodge Omni electric car was prepared for competition in an electric “stock car” 2-hour endurance event: the inaugural Solar and Electric 500 Race, April 7, 1991. This entry utilized a series-wound, direct-current 21-hp electric motor controlled by an SCR frequency and pulse width modulator. Two types of lead-acid batteries were evaluated and the final configuration was a set of 16 (6-volt each) deep-cycle units. Preparation involved weight and friction reduction; suspension modification; load, charge and temperature instrumentaltion; and electrical interlock and collision safety systems. Vehicle testing totalled 15 hours of operation. Ranges observed in testing with the final configuration were from 30 to 52 miles for loads of 175 to 90 amperes. These were nearly constant, continuous discharge cycles. The track qualifying speed (64mph) was near the 68 mph record set by the DEMI Honda at the event on the one-mile track.

A global optimization method has been developed for an engine simulation code and utilized in the search of optimal fuel injection strategies. This method uses a Lagrange interpolation function which interpolates engine output data generated at the vertices and the intermediate points of the input parameters. This interpolation function is then used to find a global minimum over the entire parameter set, which in turn becomes the starting point of a CFD-based optimization. The CFD optimization is based on a steepest descent method with an adaptive cost function, where the line searches are performed with a fast-converging backtracking algorithm. The adaptive cost function is based on the penalty method, where the penalty coefficient is increased after every line search. The parameter space is normalized and, thus, the optimization occurs over the unit cube in higher-dimensional space.

Brake energy recovery is one of the key components in today's hybrid vehicles that allows for increased fuel economy. Typically, major engineering changes are required in the drivetrain to achieve these gains. The objective of this paper is to present a concept of capturing brake energy in a mild hybrid approach without any major modifications to the drivetrain or other vehicular systems. With fuel costs rising, the additional component cost incurred in the presented concept may be recovered quickly. In today's vehicles, alternators supply the electrical power for the engine and vehicle accessories whenever the engine is running. As vehicle electrical demands increase, this load is an ever-increasing part of the engine's output, negatively impacting fuel economy. By using a regenerative device (alternator) on the drive shaft (or any other part of the power train), electrical energy can be captured during braking.

Vehicle designers make use of vehicle performance programs such as RAPTOR™ to predict the performance of concept vehicles over ranges of industry standard drive cycles. However, the accuracy of such predictions may be greatly influenced by factors requiring more specialist simulation capabilities. For example, fuel economy prediction will be heavily influenced by the performance of the engine cooling system and its impact on the vehicle's aerodynamic drag, and the load from the air-conditioning system. To improve the predictions, specialist simulation capabilities need to be applied to these aspects, and brought together with the vehicle performance calculations through co-simulation. This paper describes the approach used to enable this cosimulation and the benefits achieved by the vehicle designer.

The design and selection of a hydraulic system for a particular machine is based upon a variety of factors which include: functionality, performance, safety, cost, reliability, duty cycle, component availability, and efficiency. With higher fuel costs and requirements to reduce engine exhaust emissions, new hydraulic system configurations should be considered. Traditional hydraulic systems conssume an excessive amount of energy due to metering losses. A single pump usually supplies flow to multiple functions, with differing flow and pressure requirements resulting in excessive metering losses. The energy of mass and inertial loads is usually dissipated by metering losses. Opportunities exist for reducing metering losses by the use of multiple pumps and by using hydrostatic control of individual functions. Hydrostatic control also allows for energy recovery when used in conjunction with an energy storage system.

Three-dimensional diesel engine combustion simulations with single-step chemistry have been compared with two-step and three-step chemistry by means of the Laminar and Turbulent Characteristic Time Combustion model using the Star-CD program. The second reaction describes the oxidation of CO and the third reaction describes the combustion of H2. The comparisons have been performed for two heavy-duty diesel engines. The two-step chemistry was investigated for a purely kinetically controlled, for a mixing limited and for a combination of kinetically and mixing limited oxidation. For the latter case, two different descriptions of the laminar reaction rates were also tested. The best agreement with the experimental cylinder pressure has been achieved with the three-step mechanism but the differences with respect to the two-step and single-step reactions were small.

A quantitative relationship between inductances and operating currents of automotive electromagnetic devices was necessary for experimentally assessing the nature of the spark that occurs when a current-carrying conductor in an automobile electrical system is broken. Various automotive electromagnetic devices were obtained, and their inductances and dc operating currents were measured. A plot of the data showed, as expected, that an inverse relationship existed, and regression analysis showed that the relationship could be expressed as where L is inductance in millihenries, and I is current in amperes. This formula, which provided sufficient accuracy for the intended experiments, may be used for estimating the inductance of an automotive electromagnetic device if the current drawn by the device is known.

A modified version of the Laminar and Turbulent Characteristic Time combustion model and the Hiroyasu-Magnussen soot model have been implemented in the flow solver Star-CD. Combustion simulations of three DI diesel engines, utilizing the standard k-ε turbulence model and a modified version of the RNG k-ε turbulence model, have been performed and evaluated with respect to combustion performance and emissions. Adjustments of the turbulent characteristic combustion time coefficient, which were necessary to match the experimental cylinder peak pressures of the different engines, have been justified in terms of non-equilibrium turbulence considerations. The results confirm the existence of a correlation between the integral length scale and the turbulent time scale. This correlation can be used to predict the combustion time scale in different engines.

This paper describes the development of a generic test cell software designed to overcome many vehicle-component testing difficulties by introducing modern, real-time control and simulation capabilities directly to laboratory test environments. Successfully demonstrated in a transmission test cell system, this software eliminated the need for internal combustion engines (ICE) and test-track vehicles. It incorporated the control of an advanced AC induction motor that electrically simulated the ICE and a DC dynamometer that electrically replicated vehicle loads. Engine behaviors controlled by the software included not only the average crankshaft torque production but also engine inertia and firing pulses, particularly during shifts. Vehicle loads included rolling resistance, aerodynamic drag, grade, and more importantly, vehicle inertia corresponding to sport utility, light truck, or passenger cars.

Objective of this work is the incorporation of the flame stretch effects in an Eulerian-Lagrangian model for premixed SI combustion in order to describe ignition and flame propagation under highly inhomogeneous flow conditions. To this end, effects of energy transfer from electrical circuit and turbulent flame propagation were fully decoupled. The first ones are taken into account by Lagrangian particles whose main purpose is to generate an initial burned field in the computational domain. Turbulent flame development is instead considered only in the Eulerian gas phase for a better description of the local flow effects. To improve the model predictive capabilities, flame stretch effects were introduced in the turbulent combustion model by using formulations coming from the asymptotic theory and recently verified by means of DNS studies. Experiments carried out at Michigan Tech University in a pressurized, constant-volume vessel were used to validate the proposed approach.

The effect of flow direction towards the spark plug electrodes on ignition parameters is analyzed using an innovative spark aerodynamics fixture that enables adjustment of the spark plug gap orientation and plug axis tilt angle with respect to the incoming flow. The ignition was supplied by a long discharge high energy 110 mJ coil. The flow was supplied by compressed air and the spark was discharged into the flow at varying positions relative to the flow. The secondary ignition voltage and current were measured using a high speed (10MHz) data acquisition system, and the ignition-related metrics were calculated accordingly. Six different electrode designs were tested. These designs feature different positions of the electrode gap with respect to the flow and different shapes of the ground electrodes. The resulting ignition metrics were compared with respect to the spark plug ground strap orientation and plug axis tilt angle about the flow direction.

Vehicle-to-Grid (V2G) service has a potential to improve the reliability and stability of the electrical grid due to the ability of providing bi-directional power flow from/to the grid. However, frequent charging/discharging may impact the battery lifetime. This paper presents the analysis of battery degradation in three scenarios. In the first scenario, different battery capacities are considered. In the second scenario, the battery degradation with various depth of discharge (DOD) are studied. In the third scenario, the capacity loss due to different charging regime are compared. The charging/discharging of plug-in electric vehicles (PEVs) are simulated in a single-phase microgrid system integrated with a photovoltaics (PV) farm, an energy storage system (ESS), and ten electric vehicle service equipment (EVSE). The battery degradation model is an energy throughput model, which is developed based on the Arrhenius equation and a power law relationship between time and capacity fading.

A high voltage battery is an essential part of hybrid electric vehicles (HEVs). It is imperative to precisely estimate the state of charge (SOC) and state of health (SOH) of battery in real time to maintain reliable vehicle operating conditions. This paper presents a method of estimating SOC and SOH through the incorporation of current integration, voltage translation, and Ah-throughput. SOC estimation utilizing current integration is inadequate due to the accumulation of errors over the period of usage. Thus voltage translation of SOC is applied to rectify current integration method which improves the accuracy of estimation. Voltage translation data is obtained by subjecting the battery to hybrid pulse power characterization (HPPC) test. The Battery State of Health was determined by semi-empirical model combined with accumulated Ah-throughput method. Battery state of charge was employed as an input to estimate damages accumulated to battery aging through a real-time model.

This paper studies the nonlinear model predictive control for a power-split Hybrid Electric Vehicle (HEV) power management system to improve the fuel economy. In this paper, a physics-based battery model is built and integrated with a base HEV model from Autonomie®, a powertrain and vehicle model architecture and development software from Argonne National Laboratory. The original equivalent circuit battery model from the software has been replaced by a single particle electrochemical lithium ion battery model. A predictive model that predicts the driver’s power request, the battery state of charge (SOC) and the engine fuel consumption is studied and used for the nonlinear model predictive controller (NMPC). A dedicated NMPC algorithm and its solver are developed and validated with the integrated HEV model. The performance of the NMPC algorithm is compared with that of a rule-based controller.