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The force required to assemble automotive electrical connectors has been tested using a range of mating speeds in a controlled lab environment. This set of tests answers questions often brought up regarding how mating speed significantly influences the required applied force. Data from these evaluations show small but consistent mate force changes with assembly speed. Sealed and unsealed connectors were found to respond differently to mating speed, which is explained using a theoretical analysis. The mechanical analysis explains what forces are involved and how they are influenced by speed. Practical recommendations are given on how mate force testing should be done to assure results are as useful as possible. Results show that that mating speed has a positive correlation to peak mate force. An opposite, negative, correlation for unsealed connectors was found. Follow-on discussion explains why slow and accurate testing is preferred to testing at the actual speeds seen in the plant.

Growing concerns about the environment, energy dependency, and unstable fuel prices have increased the market share of electric vehicles. This has led to an increased demand for energy efficient routing algorithms that are optimized for electric vehicles. Traditional routing algorithms are focused on finding the shortest distance or the least time route between two points. These approaches have been working well for fossil fueled vehicles. Electric vehicles, on the other hand, require different route optimization techniques. Negative edge costs, battery power and capacity limits, as well as vehicle parameters that are only available at query time, make the task of electric vehicle routing a challenging problem. In this paper, we present a simulated solution to the energy efficient routing for electric vehicles using Particle Swarm Optimization. Simulation results show improvements in the energy consumption of the electric vehicle when applied to a start-to-destination routing problem.

In an Automotive air conditioning system, the air flow distribution in the cabin from the HVAC (Heating, ventilation and air conditioning), ducts and outlets is evaluated by the velocity achieved at driver and passenger mannequin aim points. Multiple simulation iterations are being carried out before finalizing the design of HVAC panel duct and outlets until the target velocity is achieved. In this paper, a parametric modeling of the HVAC outlet is done which includes primary and secondary vane creation using CATIA. Java macro files are created for simulation runs in STAR CCM+. ISIGHT is used as an interface tool between CATIA and STARCCM+. The vane limits of outlet and the target velocity to be achieved at mannequin aim points are defined as the boundary conditions for the analysis. Based on the optimization technique and the number of iterations defined in ISIGHT, the vane angle model gets updated automatically in CATIA followed by the simulation runs in STARCCM+.

This paper describes a comprehensive methodology for the simulation of vehicle body panel buckling in an electrophoretic coat (electro-coat or e-coat) and/or paint oven environment. The simulation couples computational heat transfer analysis and structural analysis. Heat transfer analysis is used to predict temperature distribution throughout a vehicle body in curing ovens. The vehicle body temperature profile from the heat transfer analysis is applied as an input for a structural analysis to predict buckling. This study is focused on the radiant section of the curing ovens. The radiant section of the oven has the largest temperature gradients within the body structure. This methodology couples a fully transient thermal analysis to simulate the structure through the electro-coat and paint curing environments with a structural, buckling analysis.

Automotive vehicle body electrophoretic (e-coat) and paint application has a high degree of complexity and expense in vehicle assembly. These steps involve coating and painting the vehicle body. Each step has multiple coatings and a curing process of the body in an oven. Two types of heating methods, radiation and convection, are used in the ovens to cure coatings and paints during the process. During heating stage in the oven, the vehicle body has large thermal stresses due to thermal expansion. These stresses may cause permanent deformation and weld/joint failure. Body panel deformation and joint failure can be predicted by using structural analysis with component surface temperature distribution. The prediction will avoid late and costly changes to the vehicle design. The temperature profiles on the vehicle components are the key boundary conditions used to perform structure analysis.

Forward Collision Warning (FCW) is a system intended to warn the driver in order to reduce the number of rear end collisions or reduce the severity of collisions. However, it has the potential to generate driver annoyances and unintended consequences due to high ineffectual (false or unnecessary) alarms with a corresponding reduction in the total system effectiveness. The ineffectual alarm rate is known to be closely associated with the “time to issue warning.” This results in a conflicting set of requirements. The earlier the time the warning is issued, the greater probability of reducing the severity of the impact or eliminating it. However, with an earlier warning time there is a greater chance of ineffectual warning, which could result in significant annoyance, frequent complaints and the driver's disengagement of the FCW. Disengaging the FCW eliminates its potential benefits.

Reliable testing of a mechanical system requires the procedures used for the evaluation to be repeatable and reproducible. However, it is never possible to exactly repeat or reproduce the tests that are used for evaluation. To overcome this limitation, a statistical evaluation procedure can generally be used. However, most of the statistical procedures use scalar values as input without the ability to handle vectors or time-histories. To overcome these limitations, two numerical/statistical methods for determining if the impact time-history response of a mechanical system is repeatable or reproducible are evaluated and elaborated upon. Such a system could be a vehicle, a biological human surrogate, an Anthropometric Test Device (ATD or dummy), etc. The responses could be sets of time-histories of accelerations, forces, moments, etc., of a component or of the system. The example system evaluated is the BioRID II rear impact dummy.

This paper presents a process for the selection of spring rate and pre-load for an adaptively controlled pivoting vane oil pump. The pivoting vane pump has two modes: high and low speed. A spring within the pump is installed to induce a torque that causes an adaptive displacement mechanism within the pump to move toward maximum oil chamber size. In low speed mode, two feedback regions are pressurized that produce torques that counter the spring generated torque. Together, both regions being pressurized by main oil gallery pressure tend to reduce pump displacement more at lower speeds than if only a single chamber is pressurized. At higher speeds, a solenoid switch turns off pressure to one of the feedback pressure chambers, thereby reducing feedback torque that counters spring torque. This enables higher pressure calibrations in this speed mode. In this paper, we identify a process for choosing the spring rate and pre-load that calibrates the adaptive displacement mechanism.

The concept of full vehicle simulation has been embraced by the automobile industry as it is an indispensable tool for analyzing vehicles. Vehicle loads traditionally obtained by road load data acquisition such as wheel forces are typically not invariant as they depend on the vehicle that was used for the measurement. Alternatively, virtual road load data acquisition approach has been adopted in industry to derive invariant loads. Analytical loads prior to building hardware prototypes can shorten development cycles and save costs associated with data acquisition. The approach described herein estimate realistic component load histories with sufficient accuracy and reasonable effort using full vehicle simulations. In this study, a multi-body dynamic model of the vehicle was built and simulated over digitized road using ADAMS software, and output responses were correlated to a physical vehicle that was driven on the same road.

Due to their high energy density and low self-discharge rates, lithium-ion batteries are becoming the favored solution for portable electronic devices and electric vehicles. Lithium-Ion batteries require special charging methods that must conform to the battery cells' power limits. Many different charging methods are currently used, some of these methods yield shorter charging times while others yield more charge capacity. This paper compares the constant-current constant-voltage charging method against the time pulsed charging method. Charge capacity, charge time, and cell temperature variations are contrasted. The results allow designers to choose between these two methods and select their parameters to meet the charging needs of various applications.

There is a continual need to apply heat treatment processes in innovative ways to optimize material performance. One such application studied in this research is carburizing followed by austempering of low carbon alloy steels, AISI 8620, AISI 8822 and AISI 4320, to produce components with high strength and toughness. This heat treatment process was applied in two steps; first, carburization of the surface of the parts, second, the samples were quenched from austenitic temperature at a rate fast enough to avoid the formation of ferrite or pearlite and then held at a temperature just above the martensite starting temperature to partially or fully form bainite. Any austenite which was not transformed during austempering, upon further cooling formed martensite or was present as retained austenite.

There is a growing worldwide concern regarding the environmental aspects related to the performance of a corporation and its products, whether by consumer demand or government requirements. The constant pressure for innovations and improvements related to sustainable development are current issues in everyday life of any institution that seeks to consolidate a position of acceptance and competitiveness in the global market. The automotive industry is one of the markets more involved and challenged to the demand of the environmental requirements in regards the limits of pollutant emissions and consequently fuel consumption. The European and North America vehicles already have more electrical content inside (either related to safety and comfort or even needs related to weather), which results in significantly higher consumption levels than traditionally observed in Brazil's application.

With the increased market share of electric vehicles, the demand for energy-efficient routing algorithms specifically optimized for electric vehicles has increased. Traditional routing algorithms are focused on optimizing the shortest distance or the shortest time in finding a path from point A to point B. These traditional methods have been working well for fossil fueled vehicles. Electric vehicles, on the other hand, require different route optimization techniques. Negative edge costs, battery power limits, battery capacity limits, and vehicle parameters that are only available at query time, make the task of electric vehicle routing a challenging problem. In this paper, we present an ant colony based, energy-efficient routing algorithm that is optimized and designed for electric vehicles. Simulation results show improvements in the energy consumption of electric vehicles when applied to a start-to-destination routing problem.

This paper presents the design of a hybrid powertrain damping control algorithm using the sliding mode control (SMC) scheme. Motor control-based active damping control strategy is used to ensure smooth drive line operation and provide the driver with seamless driving experience. In the case of active damping control, motor and engine speeds are measured to monitor the driveline state, and corrective motor torques are generated to dampen out drive line vibrations. Drive lines are prone to internal vibration (engine, clutches and motors) as well as external disturbances caused by road inputs. As such, fast-response actuator-based damping control systems are desirable in a hybrid powertrain application, where a torque converter is generally not used. The most significant aspect of an active damping control algorithm is the error calculation, based on proper states information, and torque determination based on the adaptive control gain applied to the nonlinear system.

This paper reports a study undertaken by the Crash Safety Working Group (CSWG) of the United States Council for Automotive Research (USCAR) to determine generic acceleration pulses for testing and evaluating advanced batteries subjected to inertial loading for application in electric passenger vehicles. These pulses were based on characterizing vehicle acceleration time histories from standard laboratory vehicle crash tests. Crash tested passenger vehicles in the United States vehicle fleet of the model years 2005-2009 were used in this study. Crash test data, in terms of acceleration time histories, were collected from various crash modes conducted by the National Highway Traffic Safety Administration (NHTSA) during their New Car Assessment Program (NCAP) and Federal Motor Vehicle Safety Standards (FMVSS) evaluations, and the Insurance Institute for Highway Safety (IIHS).

Regression models are used to understand the relative fatality risk for drivers in front-front and front-left crashes. The field accident data used for the regressions were extracted by NHTSA from the FARS database for model years 2000-2007 vehicles in calendar years 2002-2008. Multiple logistic regressions are structured and carried out to model a log-linear relationship between risk ratio and the independent vehicle and driver parameters. For front-front crashes, the regression identifies mass ratio, belt use, and driver age as statistically significant parameters (p-values less than 1%) associated with the risk ratio. The vehicle type and presence of the ESC are found to be related with less statistical significance (p-values between 1% and 5%). For front-left crashes the driver risk ratio is also found to have a log-log linear relationship with vehicle mass ratio.

This paper reports a 2010 study undertaken to determine generic acceleration pulses for testing and evaluating advanced batteries for application in electric passenger vehicles. These were based on characterizing vehicle acceleration time histories from standard laboratory vehicle crash tests. Crash tested passenger vehicles in the United States vehicle fleet of the model years 2005-2009 were used. The crash test data were gathered from the following test modes and sources: 1 Frontal rigid flat barrier test at 35 mph (NHTSA NCAP) 2 Frontal 40% offset deformable barrier test at 40 mph (IIHS) 3 Side moving deformable barrier test at 38 mph (NHTSA side NCAP) 4 Side oblique pole test at 20 mph (US FMVSS 214/NHTSA side NCAP) 5 Rear 70% offset moving deformable barrier impact at 50 mph (US FMVSS 301). The accelerometers used were from locations in the vehicle where deformation is minor or non-existent, so that the acceleration represents the “rigid-body” motion of the vehicle.

Nij, a function of upper neck forces and moment, plays a dominant role in the vehicle's star rating under the new NHTSA NCAP front impact program. This is mainly due to an artifact in the mapping of the Nij into the “risk” value used in the star rating, and the fact that the neck region is not weighted appropriately to reflect its real world significance relative to the other body regions in the NCAP rating. New test data also show that compared with the 50th male driver Nij, the 5th female passenger Nij is significantly more challenging to contain and therefore it is more dominant in the star rating. This paper describes the Hybrid III dummy head and neck impact response and provides a method to determine the external force acting on the head. The force and its acting point on the head are determined from head acceleration, angular acceleration, and the upper neck forces.

Many experiments have demonstrated that clutch overheating is a major cause of clutch deterioration. Clutch friction material deterioration not only leads to clutch failure, but also causes poor shift quality. Unfortunately, it is not practical to monitor each individual clutch temperature in a production vehicle due to high costs or technical challenges. This paper introduces a proposal for a virtual clutch temperature sensor to monitor the real time clutch temperature changes in Chrysler transmissions with PWM solenoid based control systems. Both vehicle and laboratory dynamometer (dyno) tests demonstrate that the model results match very closely with the thermocouple temperature measurements under many different driving conditions. The real time virtual temperature sensor provides a tool for clutch surface overheat protection and for design improvement and enhancement to shift quality.

In order to define and to optimize a thermal management system for a high voltage vehicular battery, it is essential to understand the environmental factors acting on the battery and their influence on battery life. This paper defines a calendar life aging model for a battery, and applies real world environmental and operating conditions to that model. Charge and usage scenarios are combined with various cooling/heating approaches. This set of scenarios is then applied to the calendar life model, permitting optimization of battery thermal management strategies. Real-world battery life can therefore be maximized, and trade-offs for grid energy conversion efficiency and fuel economy/vehicle range can be determined.