Increased fuel economy in transportation systems by use of energy management. Volume III. Real-time (hybrid computer) simulation program set.

Transportation Department, Washington, D.C.

Evaluation tests of lower neck transducer for the Hybrid III dummy. Final report.

Mode of access: Internet.

Frontal crash responses: Part 572 versus Hybrid III dummy response evaluation. Final report.

Mode of access: Internet.

Hybrid materials substitution for Oldsmobile Omega X-body components. Final report.

National Highway Traffic Safety Administration, Office of Research and Development, Washington, D.C.

Development and evaluation of Hybrid III multi-point thoracic deflection measurement sensors. Final report.

Mode of access: Internet.

A multi-modular second life hybrid battery energy storage system for utility grid applications

The modern grid system or the smart grid is likely to be populated with multiple distributed energy sources, e.g. wind power, PV power, Plug-in Electric Vehicle (PEV). It will also include a variety of linear and nonlinear loads. The intermittent nature of renewable energies like PV, wind turbine and increased penetration of Electric Vehicle (EV) makes the stable operation of utility grid system challenging. In order to ensure a stable operation of the utility grid system and to support smart grid functionalities such as, fault ride-through, frequency response, reactive power support, and mitigation of power quality issues, an energy storage system (ESS) could play an important role. A fast acting bidirectional energy storage system which can rapidly provide and absorb power and/or VARs for a sufficient time is a potentially valuable tool to support this functionality. Battery energy storage systems (BESS) are one of a range suitable energy storage system because it can provide and absorb power for sufficient time as well as able to respond reasonably fast. Conventional BESS already exist on the grid system are made up primarily of new batteries. The cost of these batteries can be high which makes most BESS an expensive solution. In order to assist moving towards a low carbon economy and to reduce battery cost this work aims to research the opportunities for the re-use of batteries after their primary use in low and ultra-low carbon vehicles (EV/HEV) on the electricity grid system. This research aims to develop a new generation of second life battery energy storage systems (SLBESS) which could interface to the low/medium voltage network to provide necessary grid support in a reliable and in cost-effective manner. The reliability/performance of these batteries is not clear, but is almost certainly worse than a new battery. Manufacturers indicate that a mixture of gradual degradation and sudden failure are both possible and failure mechanisms are likely to be related to how hard the batteries were driven inside the vehicle. There are several figures from a number of sources including the DECC (Department of Energy and Climate Control) and Arup and Cenex reports indicate anything from 70,000 to 2.6 million electric and hybrid vehicles on the road by 2020. Once the vehicle battery has degraded to around 70-80% of its capacity it is considered to be at the end of its first life application. This leaves capacity available for a second life at a much cheaper cost than a new BESS Assuming a battery capability of around 5-18kWhr (MHEV 5kWh - BEV 18kWh battery) and approximate 10 year life span, this equates to a projection of battery storage capability available for second life of >1GWhrs by 2025. Moreover, each vehicle manufacturer has different specifications for battery chemistry, number and arrangement of battery cells, capacity, voltage, size etc. To enable research and investment in this area and to maximize the remaining life of these batteries, one of the design challenges is to combine these hybrid batteries into a grid-tie converter where their different performance characteristics, and parameter variation can be catered for and a hot swapping mechanism is available so that as a battery ends it second life, it can be replaced without affecting the overall system operation. This integration of either single types of batteries with vastly different performance capability or a hybrid battery system to a grid-tie 3 energy storage system is different to currently existing work on battery energy storage systems (BESS) which deals with a single type of battery with common characteristics. This thesis addresses and solves the power electronic design challenges in integrating second life hybrid batteries into a grid-tie energy storage unit for the first time. This study details a suitable multi-modular power electronic converter and its various switching strategies which can integrate widely different batteries to a grid-tie inverter irrespective of their characteristics, voltage levels and reliability. The proposed converter provides a high efficiency, enhanced control flexibility and has the capability to operate in different operational modes from the input to output. Designing an appropriate control system for this kind of hybrid battery storage system is also important because of the variation of battery types, differences in characteristics and different levels of degradations. This thesis proposes a generalised distributed power sharing strategy based on weighting function aims to optimally use a set of hybrid batteries according to their relative characteristics while providing the necessary grid support by distributing the power between the batteries. The strategy is adaptive in nature and varies as the individual battery characteristics change in real time as a result of degradation for example. A suitable bidirectional distributed control strategy or a module independent control technique has been developed corresponding to each mode of operation of the proposed modular converter. Stability is an important consideration in control of all power converters and as such this thesis investigates the control stability of the multi-modular converter in detailed. Many controllers use PI/PID based techniques with fixed control parameters. However, this is not found to be suitable from a stability point-of-view. Issues of control stability using this controller type under one of the operating modes has led to the development of an alternative adaptive and nonlinear Lyapunov based control for the modular power converter. Finally, a detailed simulation and experimental validation of the proposed power converter operation, power sharing strategy, proposed control structures and control stability issue have been undertaken using a grid connected laboratory based multi-modular hybrid battery energy storage system prototype. The experimental validation has demonstrated the feasibility of this new energy storage system operation for use in future grid applications.

Analysis and comparative study of different converter modes in modular second life hybrid battery energy storage systems

The use of ex-transportation battery system (i.e. second life EV/HEV batteries) in grid applications is an emerging field of study. A hybrid battery scheme offers a more practical approach in second life battery energy storage systems because battery modules could be from different sources/ vehicle manufacturers depending on the second life supply chain and have different characteristics e.g. voltage levels, maximum capacity and also different levels of degradations. Recent research studies have suggested a dc-side modular multilevel converter topology to integrate these hybrid batteries to a grid-tie inverter. Depending on the battery module characteristics, the dc-side modular converter can adopt different modes such as boost, buck or boost-buck to suitably transfer the power from battery to the grid. These modes have different switching techniques, control range, different efficiencies, which give a system designer choice on operational mode. This paper presents an analysis and comparative study of all the modes of the converter along with their switching performances in detail to understand the relative advantages and disadvantages of each mode to help to select the suitable converter mode. Detailed study of all the converter modes and thorough experimental results based on a multi-modular converter prototype based on hybrid batteries has been presented to validate the analysis.

A new VRPPD model and a hybrid heuristic solution approach for e-tailing

We analyze a business model for e-supermarkets to enable multi-product sourcing capacity through co-opetition (collaborative competition). The logistics aspect of our approach is to design and execute a network system where “premium” goods are acquired from vendors at multiple locations in the supply network and delivered to customers. Our specific goals are to: (i) investigate the role of premium product offerings in creating critical mass and profit; (ii) develop a model for the multiple-pickup single-delivery vehicle routing problem in the presence of multiple vendors; and (iii) propose a hybrid solution approach. To solve the problem introduced in this paper, we develop a hybrid metaheuristic approach that uses a Genetic Algorithm for vendor selection and allocation, and a modified savings algorithm for the capacitated VRP with multiple pickup, single delivery and time windows (CVRPMPDTW). The proposed Genetic Algorithm guides the search for optimal vendor pickup location decisions, and for each generated solution in the genetic population, a corresponding CVRPMPDTW is solved using the savings algorithm. We validate our solution approach against published VRPTW solutions and also test our algorithm with Solomon instances modified for CVRPMPDTW.

Low-emission vehicle adoption in a UK local authority fleet:economic barriers and air quality benefits

Local air quality was one of the main stimulants for low carbon vehicle development during the 1990s. Issues of national fuel security and global air quality (climate change) have added pressure for their development, stimulating schemes to facilitate their deployment in the UK. In this case study, Coventry City Council aimed to adopt an in-house fleet of electric and hybrid-electric vehicles to replace business mileage paid for in employee's private vehicles. This study made comparisons between the proposed vehicle technologies, in terms of costs and air quality, over projected scenarios of typical use. The study found that under 2009 conditions, the electric and hybrid fleet could not compete on cost with the current business model because of untested assumptions, but certain emissions were significantly reduced >50%. Climate change gas emissions were most drastically reduced where electric vehicles were adopted because the electricity supply was generated by renewable energy sources. The study identified the key cost barriers and benefits to adoption of low-emission vehicles in current conditions in the Coventry fleet. Low-emission vehicles achieved significant air pollution-associated health cost and atmospheric emission reductions per vehicle, and widespread adoption in cities could deliver significant change. © The Author 2011. Published by Oxford University Press. All rights reserved.

Powertrain optimisation in a hybrid electric bus

This paper describes the use of a formal optimisation procedure to optimise a plug-in hybrid electric bus using two different case studies to meet two different performance criteria; minimum journey cost and maximum battery life. The approach is to choose a commercially available vehicle and seek to improve its performance by varying key design parameters. Central to this approach is the ability to develop a representative backward facing model of the vehicle in MATLAB/Simulink along with appropriate optimisation objective and penalty functions. The penalty functions being the margin by which a particular design fails to meet the performance specification. The model is validated against data collected from an actual vehicle and is used to estimate the vehicle performance parameters in a model-in-the-loop process within an optimisation routine. For the purposes of this paper, the journey cost/battery life over a drive cycle is optimised whilst other performance indices are met (or exceeded). Among the available optimisation methods, Powell's method and Simulated Annealing are adopted. The results show this method as a valid alternative modelling approach to vehicle powertrain optimisation. © 2012 IEEE.

Practical design considerations of cascaded hybrid battery storage systems

The high cost of batteries has led to investigations in using second-life ex-transportation batteries for grid support applications. Vehicle manufacturers currently all have different specifications for battery chemistry, arrangement of cells, capacity and voltage. With anticipated new developments in battery chemistry which could also affect these parameters, there are, as yet, no standards defining parameters in second life applications. To overcome issues relating to sizing and to prevent future obsolescence for the rest of the energy storage system, a cascaded topology with an operating envelope design approach has been used to connect together modules. This topology offers advantages in terms of system reliability. The design methodology is validated through a set of experimental results resulting in the creation of surface maps looking at the operation of the converter (efficiency and inductor ripple current). The use of a pre-defined module operating envelope also offers advantages for developing new operational strategies for systems with both hybrid battery energy systems and also hybrid systems including other energy sources such as solar power.

New integrated multilevel converter for switched reluctance motor drives in plug-in hybrid electric vehicles with flexible energy conversion

This paper presents an integrated multilevel converter of switched reluctance motors (SRMs) fed by a modular front-end circuit for plug-in hybrid electric vehicle (PHEV) applications. Several operating modes can be achieved by changing the on-off states of the switches in the front-end circuit. In generator driving mode, the battery bank is employed to elevate the phase voltage for fast excitation and demagnetization. In battery driving mode, the converter is reconfigured as a four-level converter, and the capacitor is used as an additional charge capacitor to produce multilevel voltage outputs, which enhances the torque capability. The operating modes of the proposed drive are explained and the phase current and voltage are analyzed in details. The battery charging is naturally achieved by the demagnetization current in motoring mode and by the regenerative current in braking mode. Moreover, the battery can be charged by the external AC source or generator through the proposed converter when the vehicle is in standstill condition. The SRM-based PHEV can operate at different speeds by coordinating the power flow between the generator and battery. Simulation in MATLAB/Simulink and experiments on a three-phase 12/8 SRM confirm the effectiveness of the proposed converter topology.

Hybrid power system intelligent operation and protection involving distributed architectures and pulsed loads

Efficient and reliable techniques for power delivery and utilization are needed to account for the increased penetration of renewable energy sources in electric power systems. Such methods are also required for current and future demands of plug-in electric vehicles and high-power electronic loads. Distributed control and optimal power network architectures will lead to viable solutions to the energy management issue with high level of reliability and security. This dissertation is aimed at developing and verifying new techniques for distributed control by deploying DC microgrids, involving distributed renewable generation and energy storage, through the operating AC power system. To achieve the findings of this dissertation, an energy system architecture was developed involving AC and DC networks, both with distributed generations and demands. The various components of the DC microgrid were designed and built including DC-DC converters, voltage source inverters (VSI) and AC-DC rectifiers featuring novel designs developed by the candidate. New control techniques were developed and implemented to maximize the operating range of the power conditioning units used for integrating renewable energy into the DC bus. The control and operation of the DC microgrids in the hybrid AC/DC system involve intelligent energy management. Real-time energy management algorithms were developed and experimentally verified. These algorithms are based on intelligent decision-making elements along with an optimization process. This was aimed at enhancing the overall performance of the power system and mitigating the effect of heavy non-linear loads with variable intensity and duration. The developed algorithms were also used for managing the charging/discharging process of plug-in electric vehicle emulators. The protection of the proposed hybrid AC/DC power system was studied. Fault analysis and protection scheme and coordination, in addition to ideas on how to retrofit currently available protection concepts and devices for AC systems in a DC network, were presented. A study was also conducted on the effect of changing the distribution architecture and distributing the storage assets on the various zones of the network on the system's dynamic security and stability. A practical shipboard power system was studied as an example of a hybrid AC/DC power system involving pulsed loads. Generally, the proposed hybrid AC/DC power system, besides most of the ideas, controls and algorithms presented in this dissertation, were experimentally verified at the Smart Grid Testbed, Energy Systems Research Laboratory. All the developments in this dissertation were experimentally verified at the Smart Grid Testbed.

Hybrid Power System Intelligent Operation and Protection Involving Plug-in Electric Vehicles

Two key solutions to reduce the greenhouse gas emissions and increase the overall energy efficiency are to maximize the utilization of renewable energy resources (RERs) to generate energy for load consumption and to shift to low or zero emission plug-in electric vehicles (PEVs) for transportation. The present U.S. aging and overburdened power grid infrastructure is under a tremendous pressure to handle the issues involved in penetration of RERS and PEVs. The future power grid should be designed with for the effective utilization of distributed RERs and distributed generations to intelligently respond to varying customer demand including PEVs with high level of security, stability and reliability. This dissertation develops and verifies such a hybrid AC-DC power system. The system will operate in a distributed manner incorporating multiple components in both AC and DC styles and work in both grid-connected and islanding modes. The verification was performed on a laboratory-based hybrid AC-DC power system testbed as hardware/software platform. In this system, RERs emulators together with their maximum power point tracking technology and power electronics converters were designed to test different energy harvesting algorithms. The Energy storage devices including lithium-ion batteries and ultra-capacitors were used to optimize the performance of the hybrid power system. A lithium-ion battery smart energy management system with thermal and state of charge self-balancing was proposed to protect the energy storage system. A grid connected DC PEVs parking garage emulator, with five lithium-ion batteries was also designed with the smart charging functions that can emulate the future vehicle-to-grid (V2G), vehicle-to-vehicle (V2V) and vehicle-to-house (V2H) services. This includes grid voltage and frequency regulations, spinning reserves, micro grid islanding detection and energy resource support. The results show successful integration of the developed techniques for control and energy management of future hybrid AC-DC power systems with high penetration of RERs and PEVs.

Energy Management of a Battery-Ultracapacitor Hybrid Energy Storage System in Electric Vehicles

Electric vehicle (EV) batteries tend to have accelerated degradation due to high peak power and harsh charging/discharging cycles during acceleration and deceleration periods, particularly in urban driving conditions. An oversized energy storage system (ESS) can meet the high power demands; however, it suffers from increased size, volume and cost. In order to reduce the overall ESS size and extend battery cycle life, a battery-ultracapacitor (UC) hybrid energy storage system (HESS) has been considered as an alternative solution. In this work, we investigate the optimized configuration, design, and energy management of a battery-UC HESS. One of the major challenges in a HESS is to design an energy management controller for real-time implementation that can yield good power split performance. We present the methodologies and solutions to this problem in a battery-UC HESS with a DC-DC converter interfacing with the UC and the battery. In particular, a multi-objective optimization problem is formulated to optimize the power split in order to prolong the battery lifetime and to reduce the HESS power losses. This optimization problem is numerically solved for standard drive cycle datasets using Dynamic Programming (DP). Trained using the DP optimal results, an effective real-time implementation of the optimal power split is realized based on Neural Network (NN). This proposed online energy management controller is applied to a midsize EV model with a 360V/34kWh battery pack and a 270V/203Wh UC pack. The proposed online energy management controller effectively splits the load demand with high power efficiency and also effectively reduces the battery peak current. More importantly, a 38V-385Wh battery and a 16V-2.06Wh UC HESS hardware prototype and a real-time experiment platform has been developed. The real-time experiment results have successfully validated the real-time implementation feasibility and effectiveness of the real-time controller design for the battery-UC HESS. A battery State-of-Health (SoH) estimation model is developed as a performance metric to evaluate the battery cycle life extension effect. It is estimated that the proposed online energy management controller can extend the battery cycle life by over 60%.