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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.

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.

Computational fluid dynamics of gas-fueled large-bore spark ignition engines with pre-chamber ignition can speed up the design process of these engines provided that 1) the reliability of the results is not affected by poor meshing and 2) the time cost of the meshing process does not negatively compensate for the advantages of running a computer simulation. In this work a flame propagation model that runs with arbitrary hybrid meshes was developed and coupled with the KIVA4-MHI CFD solver, in order to address these aims. The solver follows the G-Equation level-set method for turbulent flame propagation by Tan and Reitz, and employs improved numerics to handle meshes featuring different cell types such as hexahedra, tetrahedra, square pyramids and triangular prisms. Detailed reaction kinetics from the SpeedCHEM solver are used to compute the non-equilibrium composition evolution downstream and upstream of the flame surface, where chemical equilibrium is instead assumed.

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.

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.

Engineering education at the University level is enhanced by competition-based projects. The SAE Clean Snowmobile Challenge is a prime example of how competition-based engineering education benefits the small engines industry and improves the engineering talent pool of the nation in general. For the past several decades, SAE has encouraged young engineers to compete in designing off road vehicles (Baja SAE ®), small race cars (Formula SAE ®), remote control airplanes (Aero Design ®), high mileage vehicles (Supermileage ®) and robots (Walking Robot ®). Now a new competition, the SAE Clean Snowmobile Challenge ™ (CSC), based on designing a cleaner and quieter snowmobile has led to a new path for young engineers to explore the challenges of designing engines that emit less pollution and noise. The paper will summarize the results of the most recent Clean Snowmobile Challenge 2006 and document the successes of the past seven years of the Challenge.

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.

The successful implementation of a clean, quiet, four-stroke engine into an existing snowmobile chassis has been achieved. The snowmobile is easy to start, easy to drive, and environmentally friendly. The following paper describes the conversion process in detail with actual dynamometer and field test data. The vehicle is partially compliant with the proposed 2010 EPA snowmobile emissions regulations and passes an independently conducted, 74 dBA, full throttle pass-by noise test. The vehicle addresses the environmental issues surrounding snowmobiles and remains economical, with an approximate cost of $6,345.

The paper presents experimental results of a fuel cell powered electric vehicle equipped with supercapacitors. This hybrid vehicle is part of an ongoing collaboration between the Paul Scherrer Institute (PSI, Switzerland), the Swiss Federal Institute of Technology (ETHZ), and several industrial partners. It is equipped with a fuel cell system with a nominal power of 48 kW and with supercapacitors that have a storage capacity of 360 Wh. Extensive tests have been performed on a dynamometer and on the road to investigate the operating ability. The highlights of these tests were the successful trial runs across the Simplon Pass in the Swiss Alps in January 2002. The fuel cell system consists of an array of six stacks with 125 cells each and an active area of 200 cm2. The stacks are electrically connected as two parallel strings of three stacks each in series in order to match the voltage requirement of the powertrain.

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.

Verification and validation (V&V) are essential stages in the design cycle of industrial controllers to remove the gap between the designed and implemented controller. In this study, a model-based adaptive methodology is proposed to enable easily verifiable controller design based on the formulation of a sliding mode controller (SMC). The proposed adaptive SMC improves the controller robustness against major implementation imprecisions including sampling and quantization. The application of the proposed technique is demonstrated on the engine cold start emission control problem in a mid-size passenger car. The cold start controller is first designed in a single-input single-output (SISO) structure with three separate sliding surfaces, and then is redesigned based on a multiinput multi-output (MIMO) SMC design technique using nonlinear balanced realization.

Real-time control of Reactivity Controlled Compression Ignition (RCCI) during engine load and speed transient operation is challenging, since RCCI combustion phasing depends on nonlinear thermo-kinetic reactions that are controlled by dual-fuel reactivity gradients. This paper discusses the design and implementation of a real-time closed-loop combustion controller to maintain optimum combustion phasing during RCCI transient operations. New algorithms for real-time in-cylinder pressure analysis and combustion phasing calculations are developed and embedded on a Field Programmable Gate Array (FPGA) to compute RCCI combustion and performance metrics on cycle-by-cycle basis. This cycle-by-cycle data is then used as a feedback to the combustion controller, which is implemented on a real-time processor. A computationally efficient algorithm is introduced for detecting Start of Combustion (SOC) for the High Temperature Heat Release (HTHR) or main-stage heat release.

Battery State of Charge (SOC) constraints are used to prevent the battery in Hybrid Electric Vehicles (HEVs) from over-charging or over-discharging. These constraints strongly influence the power-split of the HEV. This paper presents results on how Battery State of Charge (SOC) constraints effects Lithium ion battery aging and fuel economy when using the Equivalent Consumption Minimization Strategy (ECMS). The vehicle studied is the Honda Civic Hybrid. The battery used is A123 Systems’ ANR26650 battery cell. Vehicle simulation uses multiple combinations of highway and city drive cycles. For each combination of drive cycles, nine SOC constraints ranges are used. Battery aging is evaluated using a semi-empirical model combined with the accumulated Ah-throughput method which uses, as an input, the battery SOC trajectory from the vehicle simulations. The simulation results provide insight into how SOC constraints effect fuel economy as well as battery aging.

Today's engine management systems for SI engines consist of static and dynamic control algorithms. The static functions of the engine management guarantee the correct stationary operation of the engine in all the possible operating points. The static functions are contained mainly in two lookup tables, one for the spark advance and one for the metered depending on engine speed and load. Usually these lookup tables are determined with experiments on the engine test bench. In this paper, a model-based method for the evaluation of the fuel-optimal maps for spark advance and metered fuel is described. The method can be divided into several steps: 1. Measurement and identification of all the engine parameters in a reference point (including the pressure in one cylinder) Calculation of the burn-through function (progress of the combustion) Iterative calculation of the amount of residual exhaust gas Approximation of the definitive burn-through function with the Vibe equation 2.

The paper reviews the role of drawbeads in sheet metal stamping. The design of drawbeads is discussed in depth, with treatment of different bead cross sections, bead end shapes, and bead materials. International standards and practices are included. This is followed by the historical development of the modeling of the drawbead restraining force, starting with basic equilibrium approaches, and leading to the use of the finite element method which permits the study of drawbead effects on sheet metal flow in three dimensions. Finally, the potential of active drawbeads is described based upon ongoing research which is directed toward closed-loop computer control of the stamping process through adjustment of the drawbead penetration.

The purpose of this report is to describe the process for the development of the automatically shifting manual transmission control system hardware and software to be used in the MTU Challenge X Equinox, a through-the-road parallel hybrid electric vehicle. The automatically shifting manual transmission was chosen for development, as it combines the ease of use of an automatic transmission with the fuel efficiency of a manual, while eliminating the parasitic losses in the torque converter and the transmission hydraulic pump. This report illustrates the process used to develop the software-in-the loop modeling that was developed for the initial proof of concept. In addition, it describes the development of the control strategy and hardware build for the prototype transmission. To begin the design process research was preformed on existing automatically shifting manuals and manual transmissions in general. From there vehicle subsystems were assembled using Simulink block diagrams.

This paper investigates the aging performance of the lithium ion cobalt oxide battery pack of a single shaft parallel hybrid electric vehicle (HEV) under different ambient temperatures. Varying ambient temperature of HEVs results in different battery temperature and then leads to different aging performance of the battery pack. Battery aging is reflected in the increasing of battery internal resistance and the decreasing of battery capacity. In this paper, a single shaft parallel hybrid electric vehicle model is built by integrating Automotive Simulation Model (ASM) from dSPACE and AutoLion-ST battery model from ECPower to realize the co-simulation of HEV powertrain in the common MATLAB/Simulink platform. The battery model is a physics-based and thermally-coupled battery (TCB) model, which enables the investigation of battery capacity degradation and aging. Standard driving cycle with differing ambient temperatures is tested using developed HEV model.

The steering assembly is a part of an automotive suspension system that provides control and stability. It provides control of direction, stability, and control over placement of the car. Optimization of the vehicle in weight results in enhanced performance and low fuel consumption, more so for an all-terrain race car. Optimization in this paper loosely refers to weight reduction and achieving the optimum stiffness to weight ratio of each component. This research encompasses various aspects linked to conceptualizing, designing, analysing, optimizing, and finally manufacturing the steering sub-system. Analytical calculations for mechanical design were performed using data from various experiments and jigs. CAD was developed using SolidWorks, and various analyses were performed using Altair HyperWorks. Finite Element Analysis (FEA) was primarily used to build stress plots and locate weak spots aiding optimization.