Adaptive cruise control look-ahead system for energy management of vehicles

Cruise control in motor vehicles enhances safe and efficient driving by maintaining a constant speed at a preset level. Adaptive Cruise Control (ACC) is the latest development in cruise control. It controls engine throttle position and braking to maintain a safe distance behind a vehicle in front by responding to the speed of this vehicle, thus providing a safer and more relaxing driving environment. ACC can be further developed by including the look-ahead method of predicting environmental factors such as wind speed and road slope. The conventional analytical control methods for adaptive cruise control can generate good results; however they are difficult to design and computationally expensive. In order to achieve a robust, less computationally expensive, and at the same time more natural human-like speed control, intelligent control techniques can be used. This paper presents an Adaptive Neuro-Fuzzy Inference System (ANFIS) based on ACC systems that reduces the energy consumption of the vehicle and improves its efficiency. The Adaptive Cruise Control Look-Ahead (ACC-LA) system works as follows: It calculates the energy consumption of the vehicle under combined dynamic loads like wind drag, slope, kinetic energy and rolling friction using road data, and it includes a look-ahead strategy to predict the future road slope. The cruise control system adaptively controls the vehicle speed based on the preset speed and the predicted future slope information. By using the ANFIS method, the ACC-LA is made adaptive under different road conditions (slope angle and wind direction and speed). The vehicle was tested using the adaptive cruise control look-ahead energy management system, the results compared with the vehicle running the same test but without the adaptive cruise control look-ahead energy management system. The evaluation outcome indicates that the vehicle speed was efficiently controlled through the look-ahead methodology based upon the driving cycle, and that the average fuel consumption was reduced by 3%.

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.

Effect of noise factors in energy management of series plug-in hybrid electric vehicles

It has been demonstrated that charge depletion (CD) energy management strategies are more efficient choices for energy management of plug-in hybrid electric vehicles (PHEVs). The knowledge of drive cycle as a priori can improve the performance of CD energy management in PHEVs. However, there are many noise factors which affect both drivetrain power demand and vehicle performance even in identical drive cycles. In this research, the effect of each noise factor is investigated by introducing the concept of power cycle instead of drive cycle for a journey. Based on the nature of the noise factors, a practical solution for developing a power-cycle library is introduced. Investigating the predicted power cycle, an energy management strategy is developed which considers the influence of temperature noise factor on engine performance. The effect of different environmental and geographic conditions, driver behavior, aging of battery and other components are considered. Simulation results for a modelled series PHEV similar to GM Volt show that the suggested energy management strategy based on the driver power cycle library improves both vehicle fuel economy and battery health by reducing battery load and temperature.

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.

Glass/carbon fibre hybrid composite laminates for structural applications in automotive vehicles

Light-weight structure is one of the keys to improve the fuel efficiency and reduce the environmental buden of transport vehicles (automotive and rail). While fibreglass composites have been increasingly used to replace steel in automotive industry, the adoption rate for carbon fibre composites which are much lighter, stronger and stiffere than glass fibre composites, remains low. The main reason is the high cost of carbon fibres. To further reduce vehicle weight without excessive cost increase, one technique is to incorporate carbon fibre reinforcement into glass fibre composites and innovative design by selectively reinforcing along the main load path. Glass/carbon woven fabrics with epoxy resin matrix were utilised for preparing hybrid composite laminates. The in-plane mechanical properties such as tensile and three-point-bending flexural properties were investigated for laminates with different carbon fibre volume and lay-up scheme. It is shown that hybrid composite laminates with 50% carbon fibre reinforcement provide the best flexural properties when the carbon layers are at the exterior, while the alternating carbon/glass lay-up provides the highest compressive strength.

Intelligent control and look-ahead energy management of hybrid electric vehicles

A review of the state of knowledge in the field of control and energy management in HEVs is carried out. The key innovation of the project is the development of a model of a PHEV using the real road data with an intelligent look-ahead online controller. Another novelty of this work is the method of route planning. It combines the information of vehicle sensors such as accelerometer and speedometer with the data of a GPS to create a road grade map for use within the look-ahead energy management strategy in the vehicle. For the PHEV, an adaptive cruise controller is modelled and an optimisation method is applied to obtain the best speed profile during a trajectory. Finally, the nonlinear model of the vehicle is applied with the sliding mode controller. The effect of using this controller is compared with the universal cruise controller. The stability of the system is studied and proved.

Setback distances as a conservation tool in wildlife-human interactions : testing their efficacy for birds affected by vehicles on open-coast sandy beaches

In some wilderness areas, wildlife encounter vehicles disrupt their behaviour and habitat use. Changing driver behaviour has been proposed where bans on vehicle use are politically unpalatable, but the efficacy of vehicle setbacks and reduced speeds remains largely untested. We characterised bird-vehicle encounters in terms of driver behaviour and the disturbance caused to birds, and tested whether spatial buffers or lower speeds reduced bird escape responses on open beaches. Focal observations showed that: i) most drivers did not create sizeable buffers between their vehicles and birds; ii) bird disturbance was frequent; and iii) predictors of probability of flushing (escape) were setback distance and vehicle type (buses flushed birds at higher rates than cars). Experiments demonstrated that substantial reductions in bird escape responses required buffers to be wide (> 25 m) and vehicle speeds to be slow (< 30 km h-1). Setback distances can reduce impacts on wildlife, provided that they are carefully designed and derived from empirical evidence. No speed or distance combination we tested, however, eliminated bird responses. Thus, while buffers reduce response rates, they are likely to be much less effective than vehicle-free zones (i.e. beach closures), and rely on changes to current driver behaviour

Integrated thermal and energy management of plug-in hybrid electric vehicles

In this research, the significant influence of engine and cabin thermal management on the fuel efficiency and emissions of plug-in hybrid electric vehicles is investigated. A practical solution to implement an optimal energy management strategy of plug-in hybrid electric vehicles which considers the temperature noise factor is introduced.

Are vehicles 'mobile bird hides'?: A test of the hypothesis that 'cars cause less disturbance'

We tested the 'cars cause less disturbance' hypothesis by comparing the flight-initiation distance (FID) evoked by a car versus a single walker for 38 species of waterbird (n = 657 standardised approaches). For the 15 species where we had sample size adequate for statistical testing (n ≥ 5), we found that cars elicited shorter responses after controlling for starting distance. Within-species analyses revealed that this difference was significant in 8 of 15 species. Although mean FIDs for car approaches were always shorter than FIDs toward single walkers in the remaining species (7), the tests in those species lacked sufficient power to draw meaningful conclusions. Our results provide support for the hypothesis that birds respond to cars at shorter distances. The wide taxonomic breadth of species investigated suggests that this principle may be broadly applicable, at least in waterbirds. The results of this study and the FID estimates we present will allow development of meaningful stimulus-specific buffer zones to protect waterbirds from disturbance.