Power-cycle-library-based control strategy for plug-in hybrid electric vehicles

It has been demonstrated that considering the knowledge of drive cycle as a priori in the PHEV control strategy can improve its performance. The concept of power cycle instead of drive cycle is introduced to consider the effect of noise factors in the prediction of future drivetrain power demand. To minimize the effect of noise factors, a practical solution for developing a power-cycle library is introduced. A control strategy is developed using the predicted power cycle which inherently improves the optimal operation of engine and consequently improves the vehicle performance. Since the control strategy is formed exclusively for each PHEV rather than a preset strategy which is designed by OEM, the effect of different environmental and geographic conditions, driver behavior, aging of battery and other components are considered for each PHEV. Simulation results show that the control strategy based on the driver library of power cycle would improve both vehicle performance and battery health.

Power analysis and simulation of a vehicle under combined loads

This paper presents an analytical model of fuel consumption (AMFC) to coordinate the driving power and manage the overall fuel consumption for an internal combustion engine vehicle. The model calculates the different loads applied on the vehicle including road-slope, road-friction, wind-drag, accessories, and mechanical losses. Also, it solves the combustion equation of the engine under different working conditions including various fuel compositions, excess airs and air inlet temperatures. Then it determines the contribution of each load to signify the energy distribution and power flows of the vehicle. Unlike the conventional models in which the vehicle speed needs to be given as an input, the developed model can predict the vehicle speed and acceleration under different working conditions by allowing the speed to vary within a predefined range only. Furthermore, the model indicates the ways to minimises the vehicles' fuel consumption under various driving conditions. The results show that the model has the potential to assist in the vehicle energy management.

An intelligent energy management model for a parallel hybrid vehicle under combined loads

To exploit the benefits offered by parallel HEVs, an intelligent energy management model is developed and evaluated in this paper. Despite most existing works, the developed model incorporates combined wind/drag, slope, rolling, and accessories loads to minimise the fuel consumption under varying driving conditions. A slope prediction unit is also employed. The engine and the electric motor can output power simultaneously under a heavy-load or a slopped road condition. Two simulation were conducted namely slopped-windy-prediction and slopped-windy-prediction-hybrid. The results indicate that the vehicle speed and acceleration is smoother where the hybrid component was included. The average fuel consumption for the first and second simulations were 7.94 and 7.46 liter/100 km, respectively.

Exploring creative music making as a vehicle for integrated teaching and learning

The arts have evolved with each society as a means of consolidating cultural and social identity and connecting past with future generations (Russell-Bowie, 2006, p3). Situating the arts within a broader interdisciplinary curriculum, we believe, allows students to discover and explore social issues and their relevance to students' contemporary lives. We argue that creative music making through composition promotes a deeper and more personally relevant teaching and learning experience for teacher education students, particularly when situated within an interdisciplinary framework.

The challenge for us as teacher educators' is to prepare pre-service teachers for both disciplinary and interdisciplinary learning as is required by the Victorian Essential Learning Standards (VELS). At Deakin University, in the Bachelor of Teaching (Primary/Secondary) Degree, the postgraduate unit called Humanities, Societies and Environments; Language and Music Education adopts an interdisciplinary pedagogy that encourages students to learn from each other, share content knowledge and make links between and across VELS domains.

In this paper we reflect on the possibilities exploring of creative music making to enhance the teaching and learning of social education, with particular reference to issues of environmental change. Specifically, we reflect on non-music specialist students' experiences in Semester 1, 2008 using Jeannie Baker's book Window (1991) as a platform to deliberate about the impact of urbanisation on the environment. Through dramatisation and a sonic environment students were able to both further conceptualise issues of social change and their understandings of the power of integrating music across other VELS domains.

Comparison of static and dynamic engine models on the transient performance of a passenger vehicle powertrain

This paper presents experimental and computational results obtained on the Ford Barra 190 4.0 litres I6 gasoline engine and on the Ford Falcon car equipped with this engine. Measurements of steady engine performance, fuel consumption and exhaust emissions were first collected using an automated test facility for a wide range of cam and spark timings vs. throttle position and engine speed. Simulations were performed for a significant number of measured operating points at full and part load by using a coupled Gamma Technologies GT-POWER/GT-COOL engine model for gas exchange, combustion and heat transfer. The fluid model was made up of intake and exhaust systems, oil circuit, coolant circuit and radiator cooling air circuit. The thermal model was made up of finite element components for cylinder head, cylinder, piston, valves and ports and wall thermal masses for pipes. The model was validated versus measured steady state air and fuel flow rates, cylinder pressure parameters, indicated and brake mean effective pressures, and temperature of metal, oil and coolant in selected locations. Computational results agree well with experiments, demonstrating the ability of the approach to produce fairly accurate steady state maps of BMEP and BSFC, as well as to optimize engine operation changing geometry, throttle position, cam and spark timing. Measurements of the transient performance and fuel consumption of the full vehicle were then collected over the NEDC cycle. Simulations were performed by using a coupled Gamma Technologies GT-POWER/GT-COOL/GT-DRIVE model for instantaneous engine gas exchange, combustion and heat transfer and vehicle motion. The full vehicle model is made up of transmission, driveshaft, axles, and car components and the previous engine model. The model was validated with measured fuel flow rates through the engine, engine throttle position, and engine speed and oil and coolant temperatures in selected locations. Instantaneous engine states following a time dependent demand for torque and speed differ from those obtained by interpolating steady state maps of BSFC vs. BMEP and speed. Computational results agree well with experiments, demonstrating the utility of the approach in providing a more accurate prediction of the fuel consumption over test cycles.

Direct method for optimal power management in hybrid electric vehicles

Hybrid electric vehicles are powered by an electric system and an internal combustion engine. The components of a hybrid electric vehicle need to be coordinated in an optimal manner to deliver the desired performance. This paper presents an approach based on direct method for optimal power management in hybrid electric vehicles with inequality constraints. The approach consists of reducing the optimal control problem to a set of algebraic equations by approximating the state variable which is the energy of electric storage, and the control variable which is the power of fuel consumption. This approximation uses orthogonal functions with unknown coefficients. In addition, the inequality constraints are converted to equal constraints. The advantage of the developed method is that its computational complexity is less than that of dynamic and non-linear programming approaches. Also, to use dynamic or non-linear programming, the problem should be discretized resulting in the loss of optimization accuracy. The propsed method, on the other hand, does not require the discretization of the problem producing more accurate results. An example is solved to demonstrate the accuracy of the proposed approach. The results of Haar wavelets, and Chebyshev and Legendre polynomials are presented and discussed. © 2011 The Korean Society of Automotive Engineers and Springer-Verlag Berlin Heidelberg.

Intelligent energy management for plug-in hybrid electric vehicles : the role of ITS infrastructure in vehicle electrification

The desire to reduce carbon emissions due to transportation sources has led over the past decade to the development of new propulsion technologies, focused on vehicle electrification (including hybrid, plug-in hybrid and battery electric vehicles). These propulsion technologies, along with advances in telecommunication and computing power, have the potential of making passenger and commercial vehicles more energy efficient and environment friendly. In particular, energy management algorithms are an integral part of plug-in vehicles and are very important for achieving the performance benefits. The optimal performance of energy management algorithms depends strongly on the ability to forecast energy demand from the vehicle. Information available about environment (temperature, humidity, wind, road grade, etc.) and traffic (traffic density, traffic lights, etc.), is very important in operating a vehicle at optimal efficiency. This article outlines some current technologies that can help achieving this optimum efficiency goal. In addition to information available from telematic and geographical information systems, knowledge of projected vehicle charging demand on the power grid is necessary to build an intelligent energy management controller for future plug-in hybrid and electric vehicles. The impact of charging millions of vehicles from the power grid could be significant, in the form of increased loading of power plants, transmission and distribution lines, emissions and economics (information are given and discussed for the US case). Therefore, this effect should be considered in an intelligent way by controlling/scheduling the charging through a communication based distributed control.

"Tomorrow's car" : Deakin Universities new cross vehicle that combines the best of 2 worlds

Motorbike riders are 34-times more likely to die in a crash compared to car drivers per km travelled (1). Such safety risks together with special skill requirements for the driver and much lower comfort compared to normal cars are the main reasons why motorbikes represent only a fraction of all vehicle sales in developed countries. Deakin University is developing a revolutionary cross-over fun vehicle with ultra low fuel consumption and emissions. This new vehicle generation combines the best of two worlds: the fun to drive, low cost, and small size of a scooter together with the safety, comfort and easiness to operate of a car. The result is a vehicle that is more fuel efficient than most cars or even scooters.

Various tilting cross over vehicles have been presented over the last decade that were trying to automate the tilting control of narrow vehicles to make them safer. Examples of these concepts are the Carver, Clever and in some way also the MP3 scooter from Piaggio. The problem with fully enclosed concepts like the Carver or Clever is that they require very complex and therefore also expensive tilting control systems so that the vehicles are not price competitive compared to low cost micro cars or even normal small cars. The MP3 on the other hand comes with a tilting control system which is only semi automatic so that typical car advantages - comprehensive safety features like crush zones, roll over protection, air bags, safety belts or comfort features like full weather protection including heating and cooling – can not be provided.

Deakin’s approach is quite different to the above mentioned concepts. The requirements were derived based on two different investigations: The first step was a critical evaluation of social trends and the second step was an in-depth benchmarking study of existing concepts which identified the typical strengths and weaknesses of these concepts. In a critical next step a new concept was created that addresses most of the weaknesses of existing tilting three-wheelers in a holistic approach by setting clear priority rankings for the vehicle targets, based on current trends. The priorities were set in the following order: Safety, Affordability, Fun and Efficiency (SAFE).

The key feature that enables an enclosed tilting vehicle is a fully automatic tilting control system. With an automatic tilting control system the driver does not need to put the feet on the ground to balance the vehicle when he stops, so the vehicle can be built with a full enclosure. This allows the implementation of typical car like safety features (seat belts, roll over structure, crush zones, air bags). The SafeRide™ tilting control system is a passive system that involves the driver’s balancing sense in its feedback control system. The vehicle has typical scooter like steering characteristics, where the steering is initiated through countersteering. Another safety critical design feature is the crush zone between the two front wheels which is not possible with only one front wheel or with the powertrain positioned between the front wheels, as the powertrain can’t absorb a lot of energy due to its structural stiffness and density. The passive tilting control system is quite simple and therefore makes the vehicle very affordable, an important factor for successful commercialisation.

Another advantage of integrating the human balancing senses in the feedback control of the tilting system is that the system kicks in slightly after the human balancing reacts. In some instances that can generate the typical adrenalin thrill known from riding a bike. This fun factor is quite common with many trend sports like mountain biking, surfing, roller-skating, snowboarding, or skateboarding. Some of these sports have seen very rapid growth only a short time after they have been invented. Utilising the human balancing system during driving also makes the vehicle safer as the adrenalin is produced after reaching a semi-stable driving condition that is controlled by the vehicles tilting control system, but before the vehicle reaches an unstable driving condition that can not be controlled by the vehicle but only (eventually) by the driver – if he has got the required driving skill and if he is alert enough.

Efficiency superior to most cars and scooters is achieved by the aerodynamics of a fully enclosed body structure in combination with the small frontal area of a typical scooter and the droplet shape enabled by the relatively wide front with 2 wheels and the very narrow tail with only one rear wheel. The passive tilting system also contributes to the extreme efficiency as the system only draws some small electrical power for the electronic control unit. Another feature is a low cost exhaust energy recovery system which is discussed in another paper.

Nonlinear controller design for vehicle-to-grid systems with output LCL filters

This paper presents a nonlinear controller design for vehicle-to-grid (V2G) systems with LCL output filters. The V2G systems are modeled with LCL output filters in order to eliminate harmonics for improving power qualities and the nonlinear controller is designed based on the feedback linearization. The feasibility of using the appropriate feedback linearization approaches, either partial or exact, is also investigated through the feedback linearizability of V2G systems. In this paper, partial feedback linearization is used to design the controller with a capability of sharing both active and reactive power in V2G systems. The performance of the proposed controller controller is evaluated on a single-phase full-bridge converter-based V2G system with an LCL output filter and compared to that of without any filter. Simulation results clearly demonstrate the harmonic elimination capabilities of the proposed V2G structure with the proposed control scheme.

Control and charge management of a grid-connected photovoltaic system with plug-in hybrid vehicle as energy storage

This paper presents the control and charge management strategy of a photovoltaic system (PV) with plug-in hybrid electric vehicle (PHEV) as energy storage. The hybrid energy storage system (HESS) of PHEV consists of battery and supercapacitor. A simulation model for the PV system with PHEV energy storage has been developed using Matlab/SimpowerSystems. The system consists of PV arrays, SEPIC dc-dc converter with maximum power point tracking (MPPT), hybrid battery-supercapacitor energy storage with bidirectional dc-dc converter and inverter for grid connection. A charge management algorithm for the hybrid energy storage system is proposed to control the power flows among the PV system, energy storage and the grid. Results show that the proposed power management algorithm can control the power flows in an efficient manner.

Determining the size of PHEV charging stations powered by commercial grid-integrated PV systems considering reactive power support

Due to low electricity rates at nighttime, home charging for electric vehicles (EVs) is conventionally favored. However, the recent tendency in support of daytime workplace charging that absorbs energy produced by solar photovoltaic (PV) panels appears to be the most promising solution to facilitating higher PV and EV penetration in the power grid. This paper studies optimal sizing of workplace charging stations considering probabilistic reactive power support for plug-in hybrid electric vehicles (PHEVs), which are powered by PV units in medium voltage (MV) commercial networks. In this study, analytical expressions are first presented to estimate the size of charging stations integrated with PV units with an objective of minimizing energy losses. These stations are capable of providing reactive power support to the main grid in addition to charging PHEVs while considering the probability of PV generation. The study is further extended to investigate the impact of time-varying voltage-dependent charging load models on PV penetration. The simulation results obtained on an 18-bus test distribution system show that various charging load models can produce dissimilar levels of PHEV and PV penetration. Particularly, the maximum energy loss and peak load reductions are achieved at 70.17% and 42.95% respectively for the mixed charging load model, where the system accommodates respective PHEV and PV penetration levels of 9.51% and 50%. The results of probabilistic voltage distributions are also thoroughly reported in the paper.

Static output feedback frequency stabilization of time-delay power systems with coordinated electric vehicles state of charge control

In this paper, for the first time, electric vehicles are used for both the primary and secondary frequency controls to support power plants to rapidly suppress fluctuations in the system frequency due to load disturbances. Via networked control and wide-area communication infrastructures, multiple interval time-varying delays exist in the communication channels between the control center, power plant, and an aggregation of electric vehicles. By coordinating batteries’ state of charge control, the behaviors of the vehicle owners and the uncertainties imposed by the changes of the batteries’ state of charge are taken intoconsideration. A power system model incorporating multiple time-varying delays and uncertainties is first proposed. Then, a robust static output feedback frequency controller is designed to guarantee the resulting closed-loop system stable with an H∞ attenuation level. By utilizing a novel integral inequality, namely refined-Jensen inequality, and an improved reciprocally convex combination, the design conditions are formulated in terms of tractable linear matrix inequalities which can be efficiently solved by various computational tools. The effectiveness of the proposed control scheme is verified by extensive simulations.