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When performing trajectory planning for robotic applications, there are many aspects to consider, such as the reach conditions, joint and end-effector velocities, accelerations and jerk conditions, etc. The reach conditions are dependent on the end-effector orientations and the robot kinematic structure. The reach condition feasibility is the first consideration to be addressed prior to optimizing a solution. The ‘functional’ work space or work window represents a region of feasible reach conditions, and is a sub-set of the work envelope. It is not intuitive to define. Consequently, 2D solution approaches are proposed. The 3D travel paths are decomposed to a 2D representation via radial projections. Forward kinematic representations are employed to define a 2D boundary curve for each desired end effector orientation.

The adoption of lithium-ion batteries in vehicle electrification is fast growing due to high power and energy demand on hybrid and electric vehicles. However, the battery overall performance changes with time through the vehicle life. This paper investigates the electric vehicle battery cell aging under different usages. Battery cell experimental data including open circuit voltage and internal resistance is utilized to build a typical electric vehicle model in the AVL-Cruise platform. Four driving cycles (WLTP, UDDS, HWFET, and US06) with different ambient temperatures are simulated to acquire the battery cell terminal currents. These battery cell terminal current data are inputs to the MATLAB/Simulink battery aging model. Simulation results show that battery degrades quickly in high ambient temperatures. After 15,000 hours usage in 50 degrees Celsius ambient temperature, the usable cell capacity is reduced up to 25%.

A methodology for evaluating life cycle cost of electric vehicles (EVs) to their buyers is presented. The methodology is based on an analysis of conventional vehicle costs, costs of drivetrain and auxiliary components unique to EVs, and battery costs. The conventional vehicle's costs are allocated to such subsystems as body, chassis, and powertrain. In electric vehicles, an electric drive is substituted for the conventional powertrain. The current status of the electric drive components and battery costs is evaluated. Battery costs are estimated by evaluating the material requirements and production costs at different production levels; battery costs are also collected from other sources. Costs of auxiliary components, such as those for heating and cooling the passenger compartment, are also estimated. Here, the methodology is applied to two vehicle types: subcompact car and minivan.

In June of 2002, 15 universities participated in the third year of FutureTruck, an advanced vehicle competition sponsored by the U.S. Department of Energy and Ford Motor Company. Using advanced technologies, teams strived to improve vehicle energy efficiency by at least 25%, reduce tailpipe emissions to ULEV levels, and lower greenhouse gas impact of a 2002 Ford Explorer. The competition vehicles were tested for dynamic performance and emissions and were judged in static events to evaluate the design and features of the vehicle. The dynamic events include braking, acceleration, handling, and fuel economy, while the dynamometer testing provided data for both the emissions event and the greenhouse gas event. The vehicles were scored for their performance in each event relative to each other; those scores were summed to determine the winner of the competition. The competition structure included different available fuels and encouraged the use of hybrid electric drivetrains.

The Battery Performance and Cost Model (BatPaC), developed by Argonne National Laboratory, is a versatile tool designed for lithium-ion battery (LIB) pack engineering. It accommodates user-defined specifications, generating detailed bill-of-materials calculations and insights into cell dimensions and pack characteristics. Pre-loaded with default data sets, BatPaC aids in estimating production costs for battery packs produced at scale (5 to 50 GWh annually). Acknowledging inherent uncertainties in parameters, the tool remains accessible and valuable for designers and engineers. BatPaC plays a crucial role in National Highway Transportation Traffic Safety Administration (NHTSA) regulatory assessments, providing estimated battery pack manufacturing costs and weight metrics for electric vehicles. Integrated with Argonne's Autonomie simulations, BatPaC streamlines large-scale processes, replacing traditional models with lookup tables.

To reduce development time and introduce technologies faster to the market, many companies have been turning more and more to Model Based Design. In Model Based Design, the development process centers around a system model, from requirements capture and design to implementation and test. Engineers can skip over a generation of system design processes on the basis of hand coding and use graphical models to design, analyze, and implement the software that determines machine performance and behavior. This paper describes the process implemented in Autonomie, a Plug-and-Play Software Environment, to design and evaluate component hardware in an emulated environment. We will discuss best practices and provide an example through evaluation of advanced high-energy battery pack within an emulated Plug-in Hybrid Electric Vehicle.

The purpose of this study is to provide an understanding of driver kinematics, injury mechanisms and spinal loads causing thoracolumbar spinal fractures in Indianapolis-type racing car drivers. Crash reports from 1996 to 2006, showed a total of forty spine fracture incidents with the thoracolumbar region being the most frequently injured (n=15). Seven of the thoracolumbar fracture cases occurred in the frontal direction and were a higher injury severity as compared to rear impact cases. The present study focuses on thoracolumbar spine fractures in Indianapolis-type racing car drivers during frontal impacts and was performed using driver medical records, crash reports, video, still photographic images, chassis accelerations from on-board data recorders and the analysis tool MADYMO to simulate crashes. A 50th percentile, male, Hybrid III dummy model was used to represent the driver.

Battery packs for plug-in hybrid electrical vehicle (PHEV) applications can be characterized as high-capacity and high-power packs. For PHEV battery packs, their power and electrical-energy capacities are determined by the range of the electrical-energy-driven operation and the required vehicle drive power. PHEV packs often employ high-power lithium-ion (Li-ion) pouch cells with large cell capacity in order to achieve high packing efficiency. Lithium-ion battery packs for PHEV applications generally have a 96SnP configuration, where S is for cells in series, P is for cells in parallel, and n = 1, 2 or 3. Two PHEV battery packs with 355V nominal voltage and 25-kWh nominal energy capacity are studied. The first pack is assembled with 96 70Ah high-power Li-ion pouch cells in 96S1P configuration. The second pack is assembled with 192 35Ah high-power Li-ion pouch cells in 96S2P configuration.

This paper presents the vehicle model development and validation process for the Ford Focus battery electric vehicles (BEVs) using Autonomie and test results from Advanced Powertrain Research Facility in Argonne National Laboratory. The parameters or characteristic values for the important components such as the electric machine and battery pack system are estimated through analyzing the test data of the multi cycle test (MCT) procedure under the standard ambient condition. A novel process was used to import vehicle test data into Autonomie. Through this process, a complete vehicle model of the Ford Focus BEV is developed and validated under ambient temperature for different drive cycles (UDDS, HWFET, US06 and Steady-State). The simulation results of the developed vehicle model show coincident results with the test data within 0.5% ∼ 4% discrepancies for electrical consumption.

Previous studies and on-road driving by consumers have shown that Hybrid Electric Vehicle fuel economy is very dependent on driver demand in both vehicle speed and vehicle acceleration [1]. The emerging technology of Plug-In Hybrid Vehicles (PHEV) may prove to also be more sensitivity to aggressive driver demand as compared to conventional internal combustion engine vehicles. This is due to the exceptional ability of the PHEV to minimize fuel consumption at mid to low power levels by the significant use of electric propulsion which enables engine downsizing. As vehicle speed and acceleration increase so does the power demand on the powertrain. The fuel consumption is directly affected by this increase in power demand level. To examine the fuel consumption impact of changing driver characteristics on PHEV’s, testing is conducted on two vehicles (parallel PHEV and power-split PHEV) on a four wheel chassis dynamometer at Argonne’s Advanced Powertrain Research Facility.

Impacts have been analyzed in terms of degree of injury, head injury criterion (HIC), and average acceleration as a function of time for frontal impacts against the following surfaces: 1. Rigid flat surface-fractured cadaver skull. 2. Astroturf-head drop of football-helmeted cadaver. 3. Windshield penetrating impact of a dummy. 4. Airbag-dynamic test by human volunteers. It is concluded that the linear acceleration/time concussion tolerance curve may not exist and that only impacts against relatively stiff surfaces producing impulses with short rise times can be critical. The authors hypothesize that if a head impact does not contain a critical HIC interval of less than 0.015 s, it should be considered safe as far as cerebral concussion is concerned.

Low back pain has a higher prevalence among drivers who have long term history of vehicle operations. Vehicle vibration has been considered to contribute to the onset of low back pain. However, the fundamental mechanism that relates vibration to low back pain is still not clear. Little is known about the relationship between vibration exposure, the biomechanical response, and the physiological responses of the seated human. The aim of this study was to determine the vibration frequency that causes the increase of muscle activity that can lead to muscle fatigue and low back pain. This study investigated the effects of various vibration frequencies on the lumbar and thoracic paraspinal muscle responses among 11 seated volunteers exposed to sinusoidal whole body vibration varying from 4Hz to 30Hz at 0.4 g of acceleration. The accelerations of the seat and the pelvis were recorded during various frequency of vibrations. Muscle activity was measured using electromyography (EMG).

Hybrid electric vehicle (HEV) is one of the most highly pursued technologies for improving energy efficiency while reducing harmful emissions. Thermal modeling and control play an ever increasing role with HEV design and development for achieving the objective of improving efficiency, and as a result of additional thermal loading from electric powertrain components such as electric motor, motor controller and battery pack. Furthermore, the inherent dual powertrains require the design and analysis of not only the optimal operating temperatures but also control and energy management strategies to optimize the dynamic interactions among various components. This paper presents a complete development process and simulation results for an efficient modeling approach with integrated control strategy for the thermal management of plug-in HEV in parallel-through-the road (PTTR) architecture using a flexible-fuel engine running E85 and a battery pack as the energy storage system (ESS).

The Wayne State University (WSU) EcoCAR2 student team is participating in a design competition for the conversion of a 2013 Chevrolet Malibu into a plug-in hybrid. The team created a repeatable on-road test drive route using local public roads near the university that would be of similar velocity ranges contained in the EcoCAR2 4-Cycle Drive Schedule - a weighted combination of four different EPA-based drive cycles (US06 split into city and highway portions, all of the HWFET, first 505 seconds portion of UDDS). The primary purpose of the team's local on-road route was to be suitable for testing the team's added hybrid components and control strategy for minimizing petroleum consumption and tail pipe emissions. Comparison analysis of velocities was performed between seven local routes and the EcoCAR2 4-Cycle Drive Schedule. Three of the seven local routes had acceptable equivalence for velocity (R₂ ≻ 0.80) and the team selected one of them to be the on-road test drive route.

Fuel consumption reduction on medium-duty tactical truck has and continues to be a significant initiative for the U.S. Army. The Crankshaft-Integrated-Starter-Generator (C-ISG) is one of the parallel hybrid propulsions to improve the fuel economy. The C-ISG configuration is attractive because one electric machine can be used to propel the vehicle, to start the engine, and to be function as a generator. The C-ISG has been implemented in one M1083A1 5-ton tactical cargo truck. This paper presents the experimental assessments of the C-ISG hybrid truck characteristics. The experimental assessments include all electric range for on- and off-road mission cycles and fuel consumption for the high voltage battery charging. Stationary tests related to the charging profile of the battery pack and the silent watch time duration is also conducted.

Currently, there is great interest in motorsports medicine in measuring driver head impact accelerations by adding small triaxial accelerometers to the communication earpieces worn by drivers. Various studies have attempted to validate the ability of the earpiece accelerometers to accurately measure head accelerations. Those experiments demonstrate success in being able to measure head accelerations on dummies and humans in low severity impacts and non-impact head motion. No study has been performed to ascertain the ability of the earpiece accelerometers to accurately measure rigid body head accelerations of the skull when they are mounted in a human ear canal and subjected to high severity head accelerations. This research was performed to evaluate the frequency response and coupling of the earpiece accelerometers to the human skull using post mortem human subject (PMHS) heads as the most realistic surrogate for the living human.

A series of 10 full-scale experimental simulations of pedestrian-vehicle impact was carried out using cadavers and a 95th percentile anthropomorphic dummy. The test subjects were impacted laterally and frontally at 24, 32 and 40 km/h (15, 20 and 24 mph). Each subject was extensively instrumented with miniature accelerometers, up to a maximum of 53 transducers. The nine-accelerometer scheme was used to measure angular acceleration of body segments from which it was possible to compute the head injury criterion (HIC) for cadaver head impact. A full-size Chevrolet was used as the impacting vehicle. The impact event was three-dimensional in nature during which the body segments executed complex motions. Dummy impacts were more repeatable than cadaver impacts but the response of these test subjects were quite different. The HIC was higher for head-hood impact than for head-ground impact in two of the cases analyzed.

Upper interior head impact safety is an important consideration in vehicle design and is covered under FMVSS 201. This standard generally requires that HIC(d) should not exceed 1000 when a legitimate target in the upper interior of a vehicle is impacted with a featureless Hybrid III headform at a velocity of 15 mph (6.7 m/s). As HIC and therefore HIC(d) is based on translational deceleration experienced at the CG of a test headform, its applicability is often doubted in protection against injury that can be caused due to rotational acceleration of head during impact. A study is carried out here using an improved lumped parameter model (LPM) representing headform impact for cases in which moderate to significant headform rotation may be present primarily due to the geometric configuration of targets.

Hybrid Electric Vehicle (HEV) owners have reported significantly lower fuel economy than the published estimates. Under on-road driving conditions, vehicle acceleration, speed, and stop time differ from those on the normalized test procedures. To explain the sensitivity, several vehicles, both conventional and hybrid electric, were tested at Argonne National Laboratory. The tests demonstrated that the fuel economy of Prius MY04 was more sensitive to drive-cycle variations. However, because of the difficulty in instrumenting every component, an in-depth analysis and quantification of the reasons behind the higher sensitivity was not possible. In this paper, we will use validated models of the tested vehicles and reproduce the trends observed during testing. Using PSAT, the FreedomCAR vehicle simulation tool, we will quantify the impact of the main component parameters, including component efficiency and regenerative braking.

The biomechanical response and injury tolerance of the shoulder in lateral impacts is not well understood. These data are needed to better understand human injury tolerance, validate finite element models and develop biofidelic shoulders in side impact dummies. Seventeen side impact sled tests were performed with unembalmed human cadavers. Data analyzed for this study include T1-Y acceleration, shoulder and thoracic load plate forces, upper sternum x and y accelerations, and struck side acromion x, y and z accelerations. One dimensional deflection at the shoulder level was determined from high-speed film by measuring the distance between a target on T1 and the impacted wall. Force-time response corridors were obtained for tests with 9 m/s pelvic offset, 10.5 m/s pelvic offset, 9 m/s unpadded flat wall, 6.7 m/s unpadded flat wall, 9 m/s soft padding and 9 m/s stiff padding. Maximum shoulder plate forces in unpadded 9 m/s tests (5.5 kN) were larger than in 6.7 m/s tests (3.3 kN).