Relative Fuel Economy Potential of Intelligent, Hybrid and Intelligent–Hybrid Passenger Vehicles

This chapter focuses on the relative fuel economy potential of intelligent, hybrid, and intelligent–hybrid passenger vehicles. Apart from passenger safety and large-scale traffic management, telematics is increasingly used for fuel saving. Hybrid powertrains, which represent a viable interim solution to overcome the range and battery life issues, come with the disadvantage of increased cost, as two propulsion systems have to be incorporated into one vehicle. The alternative, or complementary, solution to hybrid powertrains is the use of telematic technology whose potential in the road freight industry has already been proved. With the use of road grade prediction algorithms and global positioning system (GPS) data in the road freight industry, improvements in fuel economy of up to 3.5% and a 40% reduction in gear changes have been observed. The major advantages of hybrid powertrains include engine shutoff, when the vehicle is stationary, and regenerative braking. Although during highway driving, the hybrid vehicle does not offer fuel saving when compared to an equivalent conventional powertrain vehicle, as there is additional mass that must be carried, and the ability to recharge the batteries during regenerative braking events is minimal, the next generation of hybrid vehicles would include plug-in variants and an on-board GPS system fed into the vehicle's power management system that could be used to inform a controller about the vehicle's proximity to a likely recharge station, etc.

[1]  Lino Guzzella,et al.  Optimal control of parallel hybrid electric vehicles , 2004, IEEE Transactions on Control Systems Technology.

[2]  Wei-Bin Zhang,et al.  Demonstration of integrated longitudinal and lateral control for the operation of automated vehicles in platoons , 2000, IEEE Trans. Control. Syst. Technol..

[3]  M. Heddebaut,et al.  Broadband vehicle-to-vehicle communication using an extended autonomous cruise control sensor , 2005 .

[4]  M. Tomizuka,et al.  Control issues in automated highway systems , 1994, IEEE Control Systems.

[5]  Lino Guzzella,et al.  Vehicle Propulsion Systems: Introduction to Modeling and Optimization , 2005 .

[6]  Efstratios Skafidas,et al.  60 GHz compact integrated cross-coupled SIR-MH bandpass filter on bulk CMOS , 2008 .

[7]  David M Levinson,et al.  The Value of Advanced Traveler Information Systems for Route Choice , 2003 .

[8]  Mutasim A. Salman,et al.  Fuzzy logic control for parallel hybrid vehicles , 2002, IEEE Trans. Control. Syst. Technol..

[9]  Ali Emadi,et al.  Modeling and Simulation of Electric and Hybrid Vehicles , 2007, Proceedings of the IEEE.

[10]  Chris Manzie,et al.  Fuel economy improvements for urban driving : Hybrid vs. intelligent vehicles , 2007 .

[11]  Jan M. Maciejowski,et al.  Predictive control : with constraints , 2002 .

[12]  Erik Hellström,et al.  Look-ahead Control for Heavy Trucks to minimize Trip Time and Fuel Consumption , 2007 .

[13]  Donald E. Kirk,et al.  Optimal control theory : an introduction , 1970 .

[14]  Chris Manzie,et al.  A comparison of fuel consumption between hybrid and intelligent vehicles during urban driving , 2006 .