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Estimated engine torque is an important parameter used by automotive systems for automated transmission and clutch control. Heavy-duty engine and transmission manufacturers widely use SAE J -1939 based ECU torque calculation based on mass air/fuel flow steady state maps created during calibration of the engine for this purpose. As an alternative, to enhance the accuracy of this important control variable, a virtual flywheel torque sensor (VFTS) was developed. It measures the engine torque based on the harmonics of the instantaneous flywheel speed signal. Initial dynamometer testing showed the VFTS estimated torque values exhibited a maximum inaccuracy of 12% of the actual measured torque over the range of conditions tested. In this paper we report the results of on road truck testing of the VFTS. A loaded heavy truck with a gross vehicle weight rating of 80,000 pounds was used.

Automotive companies are constantly looking to increase the fuel efficiency, shift quality, passenger comfort, and to reduce wear and tear on the components. Most of these aspects depend on the accuracy of torque used for transmission control, which determines the required operational gear position at a given speed and road conditions. Currently, SAE J-1939 CAN bus torque estimation relies on steady state maps that are generated during the calibration of the engine for different speeds and loads. In this paper we report the development of a Virtual Flywheel Torque Sensor (VFTS) useful for real time torque measurement based on an engine speed harmonics analysis. The VFTS uses a signal from the flywheel speed sensor to estimate the flywheel angular acceleration, which and provides a proportional torque value which corresponds to torque at the flywheel.

Heavy-duty commercial vehicles consume a significant amount of energy due to their large size and mass, directly leading to vehicle operators prioritizing energy efficiency to reduce operational costs and comply with environmental regulations. One tool that can be used for the evaluation of energy efficiency in heavy-duty vehicles is the evaluation of energy efficiency using vehicle modeling and simulation. Simulation provides a path for energy efficiency improvement by allowing rapid experimentation of different vehicle characteristics on fuel consumption without the need for costly physical prototyping. The research presented in this paper focuses on using real-world, sparsely sampled telematics data from a large fleet of heavy-duty vehicles to create high-fidelity models for simulation. Samples in the telematics dataset are collected sporadically, resulting in sparse data with an infrequent and irregular sampling rate.

This paper describes the work performed in predicting and measuring the contribution of oil churning to the no-load losses of a commercial truck axle at typical running speeds. A computational fluid dynamics (CFD) analysis of the churning losses was conducted. The CFD model accounts for design geometry, operating speed, temperature, and lubricant properties. The model calculates the oil volume fraction and the torque loss caused by oil churning due to the viscous and inertia effects of the fluid. CFD predictions of power losses were then compared with no-load measurements made on a specially developed, dynamometer-driven test stand. The same axle used in the CFD model was tested in three different configurations: with axle shafts, with axle shafts removed, and with ring gear and carrier removed. This approach to testing was followed to determine the contribution of each source of loss (bearings, seals, and churning) to the total loss.

Light weight quiet small internal combustion engines that meet cost and required reliability parameters are important in the consumer product market as well as in the industrial environment. In the design of these lightweight powerplants, accurate analysis of factors which influence immediate and long-term effects is essential. Hologram interferometry is used to provide a full field view of engine cylinder wall deformations which may lead to noise, fatigue and related inefficiencies. The technique allows for the evaluation of cylinder deformation caused by thermal and mechanical loads. Static loads are applied to predict the deformation of the engine at specific points in the operating cycle.