Applicability of Federal motor vehicle standards to electric and hybrid vehicles.

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Mode of access: Internet.

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Mode of access: Internet.

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Mode of access: Internet.

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Mode of access: Internet.

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Mode of access: Internet.

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Mode of access: Internet.

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Mode of access: Internet.

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Mode of access: Internet.

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Mode of access: Internet.

Whole-Vehicle modelling of exhaust energy recovery on a diesel-electric hybrid bus

Hybrid vehicles can use energy storage systems to disconnect the engine from the driving wheels of the vehicle. This enables the engine to be run closer to its optimum operating condition, but fuel energy is still wasted through the exhaust system as heat. The use of a turbogenerator on the exhaust line addresses this problem by capturing some of the otherwise wasted heat and converting it into useful electrical energy.

This paper outlines the work undertaken to model the engine of a diesel-electric hybrid bus, coupled with a hybrid powertrain model which analysed the performance of a hybrid vehicle over a drive-cycle. The distribution of the turbogenerator power was analysed along with the effect on the fuel consumption of the bus. This showed that including the turbogenerator produced a 2.4% reduction in fuel consumption over a typical drive-cycle.

The hybrid bus generator was then optimised to improve the performance of the combined vehicle/engine package and the turbogenerator was then shown to offer a 3.0% reduction in fuel consumption. The financial benefits of using the turbogenerator were also considered in terms of fuel savings for operators. For an average bus, a turbogenerator could reduce fuel costs by around £1200 per year.

A Parametric Study Of A Turbogenerator On A Diesel-Electric Hybrid Bus

The fuel consumption of automotive vehicles has become a prime consideration to manufacturers and operators as fuel prices continue to rise steadily, and legislation governing toxic emissions becomes ever more strict. This is particularly true for bus operators as government fuel subsidies are cut or removed.

In an effort to reduce the fuel consumption of a diesel-electric hybrid bus, an exhaust recovery turbogenerator has been selected from a wide ranging literature review as the most appropriate method of recovering some of the wasted heat in the exhaust line. This paper examines the effect on fuel consumption of a turbogenerator applied to a 2.4-litre diesel engine.

A validated one-dimensional engine model created using Ricardo WAVE was used as a baseline, and was modified in subsequent models to include a turbogenerator downstream, and in series with, the turbocharger turbine. A fuel consumption map of the modified engine was produced, and an in-house simulation tool was then used to examine the fuel economy benefit delivered by the turbogenerator on a bus operating on various drive-cycles.

A parametric study is presented which examined the performance of turbogenerators of various size and power output. The operating strategy of the turbogenerator was also discussed with a view to maximising turbine efficiency at each operating point.

The performance of the existing turbocharger on the hybrid bus was also investigated; both the compressor and turbine were optimised and the subsequent benefits to the fuel consumption of the vehicle were shown.

The final configuration is then presented and the overall improvement in fuel economy of the hybrid bus was determined over various drive-cycles.

Design of alternative energy storage systems for hybrid vehicles based on statistical processing of driving cycles information

Hybrid vehicles represent the future for automakers, since they allow to improve the fuel economy and to reduce the pollutant emissions. A key component of the hybrid powertrain is the Energy Storage System, that determines the ability of the vehicle to store and reuse energy. Though electrified Energy Storage Systems (ESS), based on batteries and ultracapacitors, are a proven technology, Alternative Energy Storage Systems (AESS), based on mechanical, hydraulic and pneumatic devices, are gaining interest because they give the possibility of realizing low-cost mild-hybrid vehicles. Currently, most literature of design methodologies focuses on electric ESS, which are not suitable for AESS design. In this contest, The Ohio State University has developed an Alternative Energy Storage System design methodology. This work focuses on the development of driving cycle analysis methodology that is a key component of Alternative Energy Storage System design procedure. The proposed methodology is based on a statistical approach to analyzing driving schedules that represent the vehicle typical use. Driving data are broken up into power events sequence, namely traction and braking events, and for each of them, energy-related and dynamic metrics are calculated. By means of a clustering process and statistical synthesis methods, statistically-relevant metrics are determined. These metrics define cycle representative braking events. By using these events as inputs for the Alternative Energy Storage System design methodology, different system designs are obtained. Each of them is characterized by attributes, namely system volume and weight. In the last part the work, the designs are evaluated in simulation by introducing and calculating a metric related to the energy conversion efficiency. Finally, the designs are compared accounting for attributes and efficiency values. In order to automate the driving data extraction and synthesis process, a specific script Matlab based has been developed. Results show that the driving cycle analysis methodology, based on the statistical approach, allows to extract and synthesize cycle representative data. The designs based on cycle statistically-relevant metrics are properly sized and have satisfying efficiency values with respect to the expectations. An exception is the design based on the cycle worst-case scenario, corresponding to same approach adopted by the conventional electric ESS design methodologies. In this case, a heavy system with poor efficiency is produced. The proposed new methodology seems to be a valid and consistent support for Alternative Energy Storage System design.

Optimal Supervisory Control of Hybrid Vehicles

Hybrid vehicles (HV), comprising a conventional ICE-based powertrain and a secondary energy source, to be converted into mechanical power as well, represent a well-established alternative to substantially reduce both fuel consumption and tailpipe emissions of passenger cars. Several HV architectures are either being studied or already available on market, e.g. Mechanical, Electric, Hydraulic and Pneumatic Hybrid Vehicles. Among the others, Electric (HEV) and Mechanical (HSF-HV) parallel Hybrid configurations are examined throughout this Thesis. To fully exploit the HVs potential, an optimal choice of the hybrid components to be installed must be properly designed, while an effective Supervisory Control must be adopted to coordinate the way the different power sources are managed and how they interact. Real-time controllers can be derived starting from the obtained optimal benchmark results. However, the application of these powerful instruments require a simplified and yet reliable and accurate model of the hybrid vehicle system. This can be a complex task, especially when the complexity of the system grows, i.e. a HSF-HV system assessed in this Thesis. The first task of the following dissertation is to establish the optimal modeling approach for an innovative and promising mechanical hybrid vehicle architecture. It will be shown how the chosen modeling paradigm can affect the goodness and the amount of computational effort of the solution, using an optimization technique based on Dynamic Programming. The second goal concerns the control of pollutant emissions in a parallel Diesel-HEV. The emissions level obtained under real world driving conditions is substantially higher than the usual result obtained in a homologation cycle. For this reason, an on-line control strategy capable of guaranteeing the respect of the desired emissions level, while minimizing fuel consumption and avoiding excessive battery depletion is the target of the corresponding section of the Thesis.