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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.

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.

One-dimensional single-zone and two-zone analyses have been exercised to calculate the mass fraction burned in an engine operating on ethanol/gasoline-blended fuels using the cylinder pressure and volume data. The analyses include heat transfer and crevice volume effects on the calculated mass fraction burned. A comparison between the two methods is performed starting from the derivation of conservation of energy and the method to solve the mass fraction burned rates through the results including detailed explanation of the observed differences and trends. The apparent heat release method is used as a point of reference in the comparison process. Both models are solved using the LU matrix factorization and first-order Euler integration.

This paper deals with the dynamic characterization of an automotive shock absorber, a continuation of an earlier work [1]. The objective of this on-going research is to develop a testing and analysis methodology for obtaining dynamic properties of automotive shock absorbers for use in CAE-NVH low-to-mid frequency chassis models. First, the effects of temperature and nominal length on the stiffness and damping of the shock absorber are studied and their importance in the development of a standard test method discussed. The effects of different types of input excitation on the dynamic properties of the shock absorber are then examined. Stepped sine sweep excitation is currently used in industry to obtain shock absorber parameters along with their frequency and amplitude dependence. Sine-on-sine testing, which involves excitation using two different sine waves has been done in this study to understand the effects of the presence of multiple sine waves on the estimated dynamic properties.

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.

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.

Technologies that provide potential for significant improvements in engine efficiency include, engine downsizing/downspeeding (enabled by advanced boosting systems such as an electrically driven compressor), waste heat recovery through turbocompounding or organic Rankine cycle and 48 V mild hybridization. FEV’s Integrated Turbocompounding/Waste Heat Recovery (WHR), Electrification and Supercharging (FEV-ITES) is a novel approach for integration of these technologies in a single unit. This approach provides a reduced cost, reduced space claim and an increase in engine efficiency, when compared to the independent integration of each of these technologies. This approach is enabled through the application of a planetary gear system. Specifically, a secondary compressor is connected to the ring gear, a turbocompounding turbine or organic Rankine cycle (ORC) expander is connected to the sun gear, and an electric motor/generator is connected to the carrier gear.

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.

This paper describes the heat transfer model of a composite aluminum brake rotor and compares the predicted temperatures to dynamometer measurements taken during a 15 fade stop trial. The model is based on meshed surface geometry which is simulated using RadTherm software. Methods for realistically modeling heat load distribution, surface rotation, convection cooling and radiation losses are also discussed. A comparison of the simulation results to the dynamometer data shows very close agreement throughout the fade stop trial. As such, the model is considered valid and will be used for further Steel Clad Aluminum (SCA) rotor development.

An automobile and a tracked military vehicle were instrumented with multiple tachometers, one for each drive wheel/sprocket and operated with accelerometers mounted at suspension, chassis, and powertrain locations on the vehicles. The Time Variant Discrete Fourier Transform, TVDFT, order tracking method was then used to extract the order tracks and operating shapes estimated based on each tachometer. It is shown that under some conditions a different operating shape is excited by each of the wheels/sprockets simultaneously. This is due to the asymmetries present in the vehicles. The strengths of the TVDFT order tracking method are shown for this type of analysis, which is difficult due to the closeness, within 0.001 orders, and crossing of the orders. Benefits of using multiple tachometers and advanced order tracking methods become apparent for solving a class of noise and vibration problems.

This is the second part of a study on using port water injection to quantifiably enhance the knock performance of fuels. In the United States, the metric used to quantify the anti-knock performance of fuels is Anti Knock Index (AKI), which is the average of Research Octane Number (RON) and Motor Octane Number (MON). Fuels with higher AKI are expected to have better knock mitigating properties, enabling the engine to run closer to Maximum Brake Torque (MBT) spark timing in the knock limited region. The work done in part I of the study related increased knock tolerance due to water injection to increased fuel AKI, thus establishing an ‘effective AKI’ due to water injection. This paper builds upon the work done in part I of the study by repeating a part of the test matrix with Primary Reference Fuels (PRFs), with iso-octane (PRF100) as the reference fuel and lower PRFs used to match its performance with the help of port water injection.

This paper presents a Short Time Fourier Transform based algorithm to identify unknown parameters in fuel dynamics system during engine cold start and warm-up. A first order system is used to model the fuel dynamics in a port fuel injection engine. The feed forward transient fuel compensation controller is designed based on the identified model. Experiments are designed and implemented to verify the proposed algorithm. Different experiment settings are compared.

Large channel count data acquisition systems have seen increasing use in the acquisition and analysis of rotating machinery, these systems have the ability to generate very large amounts of data for analysis. The most common operating measurement made on powertrains or automobiles on the road or on dynamometers has become the order track measurement. Order tracking analysis can generate a very large amount of information that must be analyzed, both due to the number of channels and orders tracked. Analysis methods to efficiently analyze large numbers of Frequency Response Function (FRF) measurements have been developed and used over the last 20 years in many troubleshooting applications. This paper develops applications for several FRF based analysis methods as applied for efficient analysis of large amounts of order track data.

This paper describes a project on the dynamic characterization of automotive shock absorbers. The objective was to develop a new testing and analysis methodology for obtaining equivalent linear stiffness and damping of the shock absorbers for use in CAE-NVH low- to- mid frequency chassis models. Previous studies using an elastomer test machine proved unsuitable for testing shocks in the mid-to-high frequency range where the typical road input displacements fall within the noise floor of the elastomer machine. Hence, in this project, an electrodynamic shaker was used for exciting the shock absorbers under displacements less than 0.05 mm up to 500 Hz. Furthermore, instead of the swept sine technique, actual road data were used to excite the shocks. Equivalent linear spring-damper models were developed based on least-squares curve-fitting of the test data.

As the world searches for ways to reduce humanity’s impact on the environment, the automotive industry looks to extend the viable use of the gasoline engine by improving efficiency. One way to improve engine efficiency is through more effective control. Torque-based control is critical in modern cars and trucks for traction control, stability control, advanced driver assistance systems, and autonomous vehicle systems. Closed loop torque-based engine control systems require feedback signal(s); indicated mean effective pressure (IMEP) is a useful signal but is costly to measure directly with in-cylinder pressure sensors. Previous work has been done in torque and IMEP estimation using crankshaft acceleration and ion sensors, but these systems lack accuracy in some operating ranges and the ability to estimate cycle-cycle variation.

The Electronic Control Unit (ECU) of an Electric Power Steering (EPS) system is a core device to decide how much assistance an electric motor applies on a steering wheel. The EPS ECU plays an important role in EPS systems. The effectiveness of an ECU needs to be thoroughly tested before mass production. Hardware-in-the-loop simulation provides an efficient way for the development and testing of embedded controllers. This paper focuses on the development of a HiL system for testing EPS controllers. The hardware of the HiL system employs a dSPACE HiL simulator. The EPS plant model is an integrated model consisting of a Vehicle Dynamics model of the dSPACE Automotive Simulation Model (ASM) and the Nexteer Steering model. The paper presents the design of an EPS HiL system, the simulation of sensors and actuators, the functions of the ASM Vehicle Dynamics model, and the integration method of the ASM Vehicle Dynamics model with a Steering model.

Flexibility and backlash of vehicle drivelines typically cause unwanted oscillations and noise, known as shuffle and clunk, during tip-in and tip-out events. Computationally efficient and accurate driveline models are necessary for the design and evaluation of torque shaping strategies to mitigate this shuffle and clunk. To accomplish these goals, this paper develops a full-order physics-based model and uses this model to develop a reduced-order model (ROM), which captures the main dynamics that influence the shuffle and clunk phenomena. The full-order model (FOM) comprises several components, including the engine as a torque generator, backlash elements as discontinuities, and propeller and axle shafts as compliant elements. This model is experimentally validated using the data collected from a Ford vehicle. The validation results indicate less than 1% error between the model and measured shuffle oscillation frequencies.

This research investigates the energy savings achieved through eco-driving controls in connected and automated vehicles (CAVs), with a specific focus on the influence of powertrain characteristics. Eco-driving strategies have emerged as a promising approach to enhance efficiency and reduce environmental impact in CAVs. However, uncertainty remains about how the optimal strategy developed for a specific CAV applies to CAVs with different powertrain technologies, particularly concerning energy aspects. To address this gap, on-track demonstrations were conducted using a Chrysler Pacifica CAV equipped with an internal combustion engine (ICE), advanced sensors, and vehicle-to-infrastructure (V2I) communication systems, compared with another CAV, a previously studied Chevrolet Bolt electric vehicle (EV) equipped with an electric motor and battery.