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General Motors shall introduce a new rear wheel drive eight speed automatic transmission, known as the 8L90, in the 2015 Chevrolet Corvette. The rated turbine torque capacity is 1000 Nm. This transmission replaces the venerable 6L80 six speed automatic. The objectives behind creation of this transmission are improved fuel economy, performance, and NVH. Packaging in the existing vehicle architecture and high mileage dependability are the givens. The architecture is required to offer low cost for a rear drive eight speed transmission while meeting the givens and objectives. An eight speed powerflow, invented by General Motors, was selected. This powerflow yields a 7.0 overall ratio spread, enabling improved launch capability because of a deeper first gear ratio and better fuel economy due to lower top gear N/V capability, relative to the 6L80. The eight speed ratios are generated using four simple planetary gearsets, two brake clutches, and three rotating clutches.

This paper presents a methodology to represent automatic transmission clutch-to-clutch shift dynamics with a two degree of freedom, lumped inertia model. The method of reducing the automatic transmission to a lumped, two inertia model as a function of shift and input shaft acceleration is detailed using a full kinematic representation of the automatic transmission. For a given clutch-to-clutch shift maneuver there are two dependent equations that utilize the two lumped inertias and represent the response of the transmission system from input to output shaft. Applicability of the method is shown for planetary automatic and layshaft dual clutch transmissions. Typical clutch-to-clutch shift maneuvers are illustrated with the two inertia model for power on upshifts and downshifts.

A dog clutch, if successfully implemented in an automatic transmission, provides better packaging and the potential for improved fuel economy. The technical requirements for this concept are examined through modeling and simulation. As a first step, a physics-based component level model is developed that provides an understanding of the basic contact and impact dynamics. The model is compared to a built-in AMESim block to establish confidence. This component level model is then integrated into a powertrain system model within the AMESim environment. As a test bed, the powertrain model is exercised to simulate a friction plate to dog clutch shift in a 6-speed automatic transmission. The analysis helps to define the slip speed target at the onset of the dog clutch engagement while ensuring shift requirements are met. Finally, the model is validated by comparing the simulated results with measured dynamometer data.

This investigation utilizes a DFSS analysis approach to determine automatic transmission gear content required to minimize fuel consumption for various powertrain - vehicle systems. L18 and L27 inner arrays with automatic transmission design and shift pattern constraint parameters were varied to determine their relative influence on fuel consumption. An outer noise array consisting of two vehicles with various engines, final drive ratios and legislated emissions test cycles was used to make a robust transmission selection based on minimizing fuel consumption. The full details of the DFSS analysis method and assumptions are presented along with a detailed examination of the results. With respect to transmission design parameters, parasitic spinloss and gear mesh efficiency were found to be most important followed by the number of gears. The DFSS analysis further revealed that unique transmission design formulations are potentially required for widely varying engines.

As the number of fixed gear ratios in automatic transmissions continues to increase in the pursuit of powertrain system efficiency, particular consideration must continue to be focused on optimizing the design for shifting performance. This investigation focuses on the effect of shift time on the performance attributes of shift quality, durability, on schedule fuel consumption and enablers to further reduce shift time. A review of fundamental design features that enable reduced shift times in both planetary and dual clutch transmissions is presented along with key operating features of both the transmission and engine/prime mover. A lumped parameter metric is proposed to assess and compare the upshift controllability of new transmission architectures and powerflows using simple analysis. The durability of fast shift times during performance maneuvers are quantified through calculation of shifting clutch energy and power from analysis and form measurements on a powertrain dynamometer.

This investigation utilizes energy analysis and statistical methods to optimize step gear automatic transmissions gear selection for fuel consumption. A full factorial matrix of simulations using energy analysis was performed to determine the optimal number of gears and gear ratios that provide the best fuel consumption performance for a particular vehicle - engine application. The full factorial matrix setup as a design of experiment (DOE) was applied to five vehicle applications, each with two engines to examine the potential differences that variations in road load and engine characteristics might have on optimal transmission gearing selection. The transmission gearing options considered in the DOE were number of gears, launch gear ratio and top gear ratio. Final drive ratio was also included due to its global influence on vehicle performance and powertrain operating speeds and torque.

General Motors has introduced a new front wheel drive seven speed dry dual clutch automatic transmission in 2014. The 250 Nm input torque rated gear box was designed and engineered for a global market in both front wheel drive and all-wheel drive configurations. The transmission has integrated start/stop capability enabled by the use of an electric motor driven pump and a pressurized accumulator. The architecture selected was chosen for optimization of packaging, fuel economy, mass, shift pleasability, and NVH. High mileage durability and world class drivability were the cornerstone deliverables during the engineering and design process Fuel efficiency is estimated to be 3% - 10% improvement over a conventional six speed automatic transmission. FWD variant wet mass of 78.1 kg was achieved through the rigorous engineering processes used to optimize the transmission system.

Development of the next generation internal combustion engines and automatic transmissions for automotive applications is a mandatory powertrain engineering activity required now and in the coming years to meet forthcoming global emissions regulations. This paper details a preliminary investigation into possible synergies for fuel consumption reduction considering emerging automotive technologies integrated into the next generation combustion engine and automatic transmission architectures. A range of hypothetical gasoline engines were created and paired with a generalized set of step gear automatic transmissions designed to meet the performance requirements of high volume longitudinal full size truck application. These designs were then run through a design of experiments orthogonal array for prediction of fuel consumption on the WLTP test schedule and stand still acceleration to 100 kph.

The first set of SAE J2643 Standard Reference Elastomers (SRE) was developed in 2004. It was composed of a group of 10 compounds covering multiple elastomer families. Since then, more advanced materials from many elastomer families have been introduced to the automotive industry. The purpose of this study is to add a few more reference compounds to SAE J2643, to enhance the portfolio on FKM, AEM and ACM to reflect advancements in elastomer technology, and make it suitable for a variety of fluids, such as transmission fluid and engine oil. Fourteen standard elastomer compounds were involved in this study, covering various materials currently used in automotive powertrain static and dynamic sealing applications. Participants include OEMs, major rubber manufacturers, a fluid additive company and an independent lab. Manufacturers of each test compound provided formulations, designated ingredients from defined sources, and detailed mixing and molding procedures.

This paper discusses steps for identifying, evaluating and recommending a quantifiable design metric or metrics for Side Airbag (SAB) development. Three functionally related and desirable attributes of a SAB are assumed at the onset, namely, effective SAB coverage, load distribution and efficient energy management at a controlled force level. The third attribute however contradicts the “banana shaped” force-displacement response that characterizes the ineffective energy management reality of most production SAB. In this study, an estimated ATD to SAB interaction energy is used to size and recommend desired force-deformation characteristic of a robust energy management SAB. The study was conducted in the following three phases and corresponding objectives: Phase 1 is a SAB assessment metric identification and estimation, using a uniform block attached to a horizontal impact machine.

Environmental concerns and government regulations are factors that have led to an increased focus on fuel economy in the automotive industry. This paper identifies a method used to improve the efficiency of a front-wheel-drive (FWD) automatic transmission. In order to create improvements in large complex systems, it is key to have a large scope, to include as much of the system as possible. The approach taken in this work was to use Design for Six Sigma (DFSS) methodology. This was done to optimize as many of the front-wheel-drive transmission components as possible to increase robustness and efficiency. A focus of robustness, or consistency in torque transformation, is as important as the value of efficiency itself, because of the huge range of usage conditions. Therefore, it was necessary to find a solution of the best transmission component settings that would not depend on specific usage conditions such as temperatures, system pressures, or gear ratio.

This work analyzes the lubricant supply to critical regions of needle roller bearing of an automatic transmission. The needle roller bearing is a critical component of an automatic transmission and it has several rotating cylindrical needle rollers that are having relative motion with inner surface of the pinion. Supply of lubricant to the needle roller bearings is very essential to prevent failure of the bearings due to frictional contact between rollers and inner surface of pinion. The supply of lubricant to the needle roller bearings depends on the location of oil supply hole. Lubricant supply to the needle roller bearings of an automatic transmission is studied using commercial 3D Computational Fluid Dynamics (CFD) software for different oil supply positions. CFD simulation is performed for the region between the pinion supply hole and end of the needle bearings including all needles. Lubricant is supplied to the needle bearing from the pinion pin oil supply hole.

Interference assessments of a stepped-radius power-train component moving within a deformed stepped bore often arise during engine and transmission development activities. For example, when loads are applied to an engine block, the block distorts. This distortion may cause a cam or crankshaft to bind or wear prematurely in its journals as the part rotates within them. Within an automatic transmission valve body, care must be taken to ensure valve body distortion under oil pressure, assembly, and thermal load does not cause spool valves to stick as they translate within the valve body. In both examples, the mechanical scenario to be assessed involves a uniform or stepped radius cylindrical part maintaining a designated clearance through a correspondingly shaped but distorted bore. These distortions can occur in cross-sections (“out-of-round”) or along the bore (in an “s” or “banana” shaped distortions).

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.

Due to increased demand for improved fuel economy and reduction in CO2 emissions, active grille shutter (AGS) has been considered as one option to increase fuel economy by reducing vehicle drag resistance. An AGS system will allow airflow through the grille when demand on cooling system or air conditioning system is high. Under conditions of light load and moderate ambient temperatures and humidity, the grille does not have to be fully open. A reduction in the effective grille size opening can be achieved by either partially or fully closing the grille through a stepped speed motor actuator. When the grille opening size is reduced, under-hood airflow will decrease. Therefore, the operating points for the grille shutter should take into account the effect of temperature rise for under-hood and underbody components and the performance of the cooling and climate control systems.

The need for improved vehicle energy efficiency has increased greatly in recent years along with regulatory fuel economy standards. One key aspect of energy efficiency for both conventional and alternative propulsion vehicles is the energy efficiency of the electrical architecture. In the design of electrical architectures there are several techniques available to increase the energy efficiency. One technique is to manage CAN serial data communication by using Partial Networks. This paper describes a model based approach for simulating the vehicle network behavior when CAN Partial Networking is used as the strategy for need based ECU activation. The simulation results will in turn provide ECU power consumption data to support various electrical architecture design decisions.

For the conventional 6 speed automatic transmission with engine stop-start powertrain, an electrically-driven auxiliary pump is implemented to maintain the transmission line pressure as required to lock-up the CB1234 clutch during engine auto-stop conditions. Upon releasing the brake pedal, the transmission engages into first gear with the objective to accelerate the vehicle in a responsive manner. In this study, a novel normally-engaged dual-piston clutch concept is designed to keep the CB1234 clutch locked-up during engine auto-stop conditions with the intention to eliminate the auxiliary pump without compromising vehicle performance. This dual piston clutch concept requires a relatively low line pressure to release the normally-engaged clutch when needed, thus, minimizing the hydraulic pumping work. To explore the functionality of this concept under a wide-open-throttle (WOT) auto-start transition, modeling and simulation of the normally-engaged dual-piston clutch is completed.

Rapidly increasing customer, financial, and regulatory pressures are creating clear changes in the calculus of vehicle design for modern automotive OEM's (Original Equipment Manufacturers). Customers continue to demand shorter product lifecycles; the increasingly competitive global market exerts pressure to reduce costs in all stages of development; and environmental regulations drive a continuous need to reduce mass and energy consumption. OEM's must confront these challenges while continuing to satisfy the customer. The foundation to meeting these challenges includes: (1) Continued development of objective metrics to quantify performance; (2) Frontloading vehicle design content and performance synthesis; (3) A precise understanding of the customer and their performance preferences under diverse usage conditions. These combined elements will enable products better optimized amongst competing (and often contradictory) imperatives.

The present paper reports on a study of the HVAC energy usage for an EREV (extended range electric vehicle) implementation of a localized cooling/heating system. Components in the localized system use thermoelectric (TE) devices to target the occupant's chest, face, lap and foot areas. A novel contact TE seat was integrated into the system. Human subject comfort rides and a thermal manikin in the tunnel were used to establish equivalent comfort for the baseline and localized system. The tunnel test results indicate that, with the localized system, HVAC energy savings of 37% are achieved for cooling conditions (ambient conditions greater than 10 °C) and 38% for heating conditions (ambient conditions less than 10 °C), respectively based on an annualized ambient and vehicle occupancy weighted method. The driving range extension for an electric vehicle was also estimated based on the HVAC energy saving.

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.