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A simulation framework with a validated system model capable of estimating fuel consumption is a valuable tool in analysis and design of the hybrid vehicles. In particular, the framework can be used for (1) benchmarking the fuel economy achievable from alternate hybrid powertrain technologies, (2) investigating sensitivity of fuel savings with respect to design parameters (for example, component sizing), and (3) evaluating the performance of various supervisory control algorithms for energy management. Presenter Chinmaya Patil, Eaton Corporation

This paper discusses the effect of torque vectoring differential on improving vehicle handling and stability performance. The torque vectoring concept has been analyzed. The vehicle discussed in this paper is an AWD vehicle with torque vectoring differential in the rear and a torque biasing center differential. First, simulation results with vehicle model in CarSim® and torque vectoring control algorithm in Matlab®/Simulink® is discussed. Then, experimental results for vehicle tested at winter and summer test facility is presented. Both simulation and experimental results demonstrate the effectiveness of torque vectoring differential on vehicle handling & stability.

A simulation framework with a validated system model capable of estimating fuel consumption is a valuable tool in analysis and design of the hybrid vehicles. In particular, the framework can be used for (1) benchmarking the fuel economy achievable from alternate hybrid powertrain technologies, (2) investigating sensitivity of fuel savings with respect to design parameters (for example, component sizing), and (3) evaluating the performance of various supervisory control algorithms for energy management. This paper describes such a simulation framework that can be used to predict fuel economy of series hydraulic hybrid vehicle for any specified driver demand schedule (drive cycle), developed in MATLAB/Simulink. The key components of the series hydraulic hybrid vehicle are modeled using a combination of first principles and empirical data. A simplified driver model is included to follow the specified drive cycle.

The approach towards building hybrid vehicles has evolved with time and requirements. What used to be direct prototype building activity has moved towards building mathematical models before the actual prototypes are built. These models are utilized in optimizing component sizes, design and calibrate controllers and to estimate fuel economy improvements. If model results show promise, the actual prototype building activity is started. But modeling of vehicles still has a long way to go before aligning with businesses and aiding them as decision making tools on R&D investments. The reason being - the model building activity itself is prolonged and expensive. In addition to this, a lot of proprietary information such as component efficiency maps is required in order to build the model. In absence of these component level data, extensive testing becomes necessary where again vast amounts of resources have to be allocated.

New regulations, rising fuel costs and environmental concerns are driving significant improvement in heavy duty truck aerodynamics and rolling resistance that fundamentally change the power needs of heavy duty trucks. Furthermore, exhaust energy recovery technology is evolving and driving a change in the power management strategies. Together with advances in hybrid technology, these changes open the potential for a cost-effective line haul hybrid line of trucks. This paper will present a simulation study that was performed in order to evaluate the potential fuel economy benefits of a heavy duty powertrain for commercial vehicles. The architecture includes hybrid electric components paired with a waste heat recovery system. The electric energy can be used to reduce engine load during peak power requests. The sources for the electric energy are both braking energy regeneration as well as conversion of waste heat to electricity via a high speed generator.

A 300 mile-range automotive battery pack is comprised of many individual cells connected in series/parallel to make up the required voltage, energy, and power. The cell groupings can take the form of parallel strings of series cell groups (S-P), series string of parallel cell groups (P-S), or a hybrid of the two. Though the different battery configurations deliver identical output voltage and energy, they exhibit varying cell level behaviors due to differing electrical structure, particularly when cell imbalance occurs. In this work, we explore the relative merits of various cell grouping configurations using a model-based approach. The emphasis of the study is to evaluate the impact of electrical variation between cell-to-cell, originating from cell manufacturing process variation, battery assembly (laser tab bonding) process variation or from normal operation, on the performance of the battery pack. A first-order equivalent circuit model is used to represent a lithium-ion cell.