Nima Ghaviha

Flow batteries use potential in heavy vehicles

Although batteries have been used in personal vehicles for more than a hundred years, the cost of the technology, limitation in range, absence of sufficient recharging infrastructure and rapid development of internal combustion engines during the mid-twentieth century limited its use to very niche applications. More recently, a global need for reducing CO2 emissions from fossil fuel usage and the great developments in power systems as well as in battery technology offers electric vehicles the possibility to return to the market, not just for personal use but also for a wide variety of transportation applications. In the present paper, a feasibility study for using flow batteries in heavy vehicles, more specifically, construction equipment is presented. The authors used measured energy demand profiles for different operation conditions of a wheel loader and developed a simulation model for a vanadium redox flow battery to test the performance of this vehicle using a flow battery. Additionally, the authors did a short theoretical analysis for the potential for flow batteries in train transportation, focusing on the requirements and limitations of the technology for this application.

Speed profile optimization of an electric train with on-board energy storage and continuous tractive effort

Electric traction system is the most energy efficient traction system in railways. Nevertheless, not all railway networks are electrified, which is due to high maintenance and setup cost of overhead lines. One solution to the problem is battery-driven trains, which can make the best use of the electric traction system while avoiding the high costs of the catenary system. Due to the high power consumption of electric trains, energy management of battery trains are crucial in order to get the best use of batteries. This paper suggests a general algorithm for speed profile optimization of an electric train with an on-board energy storage device, during catenary-free operation on a given line section. The approach is based on discrete dynamic programming, where the train model and the objective function are based on equations of motion rather than electrical equations. This makes the model compatible with all sorts of energy storage devices. Unlike previous approaches which consider trains with throttle levels for tractive effort, the new approach considers trains in which there are no throttles and tractive effort is controlled with a controller (smooth gliding handle with no discrete levels). Furthermore, unlike previous approaches, the control variable is the velocity change instead of the applied tractive effort. The accuracy and performance of the discretized approach is evaluated in comparison to the formal movement equations in a simulated experimented using train data from the Bombardier Electrostar series and track data from the UK.

Joint optimization of multiple train speed profiles

Energy efficiency of train operations is a critical issue for the electrical railway transportation, considering that one of the main benefits of this transportation mode is the lower environmental impact. A possible technology which decreases energy consumption is the reuse of the recovered energy from the braking system. Although have been made significant efforts to find efficient solutions in terms of driving strategies, timetable optimization etc, the potential of energy recovery from the braking system is still unexplored. In this paper, we consider the problem of joint optimization of multiple train speed profiles, which operate in the same power section, in order to increase the overall energy recovered from the braking system. We propose a Markov Decision Process formulation, which models the continuous space movements of the trains as stochastic transitions on discrete states, determined by train operations and electrical properties of the electrical network.

Battery Technologies for Transportation Applications

More than a fifth of the greenhouse emissions produced worldwide come from the transport sector. Several initiatives have been developed over the last few decades, aiming at improving vehicles’ energy conversion efficiency and improve mileage per liter of fuel. Most recently, electric vehicles have been brought back into the market as real competitors of conventional vehicles. Electric vehicle technology offers higher conversion efficiencies, reduced greenhouse emissions, low noise, etc. There are, however, several challenges to overcome, for instance: improving batteries’ energy density to increase the driving range, fast recharging, and initial cost. These issues are addressed on this chapter by looking in depth into both conventional and non-conventional storage technologies in different transportation applications.