Least costly energy management for series hybrid electric vehicles

Energy management of plug-in Hybrid Electric Vehicles (HEVs) has different challenges from non-plug-in HEVs, due to bigger batteries and grid recharging. Instead of tackling it to pursue energetic efficiency, an approach minimizing the driving cost incurred by the user - the combined costs of fuel, grid energy and battery degradation - is here proposed. A real-time approximation of the resulting optimal policy is then provided, as well as some analytic insight into its dependence on the system parameters. The advantages of the proposed formulation and the effectiveness of the real-time strategy are shown by means of a thorough simulation campaign

HEURISTICS AND LOWER BOUND FOR ENERGY MANAGEMENT IN HYBRID-ELECTRIC VEHICLES

International audienc

Energy management for vehicular electric power systems

The electric energy consumption in passenger vehicles is rapidly increasing. To limit the associated increase in fuel consumption, an energy management system has been developed. This system exploits the fact that the losses in the internal combustion engine vary with the operating point, and uses the possibility to temporarily store electric energy in a battery, such that electric energy is only produced at moments when it is cheap to generate. To come to a practically applicable solution, a vehicle model is derived, containing only the component characteristics relevant for this application. The energy management problem is formulated as an optimization problem. The fuel consumption over a driving cycle is minimized, while respecting physical limitations of the components and maintaining an acceptable energy level of the battery. Several optimization methods are studied to come to a solution. The dynamic optimization problem is solved using Dynamic Programming. After rewriting it as a static optimization problem and approximating the cost function by a quadratic function, the problem is solved using Quadratic Programming, which requires less computation time. A real-time implementable strategy has been derived from the Quadratic Programming problem, that does not require a prediction of the future driving cycle. This strategy compares the current cost of producing electric energy with the estimated average cost. By adapting the average cost based on the energy level of the battery, it is ensured that the battery energy level will remain around the desired value. Simulations show that a fuel reduction up till 2% can be obtained on a conventional vehicle without major hardware changes. Higher reductions are possible on the exhaust emissions. To predict and explain the amount of fuel reduction that can be obtained with a given vehicle configuration, a set of engineering rules is derived based on typical component characteristics. Their results correspond reasonably well with the simulations. An advanced power net topology is studied which contains both a battery and an ultracapacitor that are connected by a DC-DC converter and a switch. Because of the increased complexity, this system is modeled using linear and piecewise linear approximations of the component characteristics, such that the energy management problem can be casted as a Linear Programming problem. The discrete switch makes it a Mixed Integer Linear Programming Problem. A realtime strategy, similar to the strategy for the conventional power net, has been derived. The addition fuel reduction that is obtained with the dual storage power net is small, because the maximum profit that can be obtained with an ideal lossless battery is not much higher than with a normal battery. Subsequently, hybrid electric vehicles are studied that use an Integrated Starter Generator which can be used for generating electric power and for vehicle propulsion. Several conSummary figurations are studied with respect to their potential fuel reduction. Configurations that enable start-stop operation of the engine obtain a much higher fuel reduction, up to 40%. The controllers are tested in real-time on a Hardware-in-the-Loop environment, where a vehicle simulation model is combined with existing electric components. It is shown that the electric power setpoints provided by an energy management strategy can be realized in practice

Optimal Co-Design of Microgrids and Electric Vehicles: Synergies, Simplifications and the Effects of Uncertainty.

The burgeoning electrification of automobiles is causing convergence of the transportation and electrical power systems. This is visible in localized micropower systems, or microgrids, that supply plug-in vehicles. Though each system is designed by a separate industry, the need to reduce petroleum use and greenhouse gas emissions directs us to study the interface between these systems and develop methods to design both systems simultaneously. A method is presented for optimal co-design of a microgrid and electric vehicles using a nested optimal dispatch problem to solve for the operation of the microgrid and vehicles. This nested structure is implemented within a sequential optimization and reliability analysis loop to solve for the desired system reliability given uncertainties in the power load and solar power supply. The method is demonstrated for the case of co-designing a military microgrid and its all-electric tactical vehicles. The co-design approach results in a combined system design that minimizes capital investment and operating costs while meeting the reliability and performance requirements of both systems. The electric vehicles are shown to increase system reliability by providing energy storage without compromising their driving performance, and this support is shown to be robust to changes in the vehicle plug-in scheduling. The resulting optimal designs are highly-dependent on the input parameters, such as fuel cost and cost of capital equipment. For scenarios with high fuel costs and low battery prices, the co-design systems diverges significantly from separately-designed systems, resulting in improved performance and lower total costs.Ph.D.Mechanical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/91403/1/johnjohn_1.pd

Post-Westgate SWAT : C4ISTAR Architectural Framework for Autonomous Network Integrated Multifaceted Warfighting Solutions Version 1.0 : A Peer-Reviewed Monograph

Police SWAT teams and Military Special Forces face mounting pressure and challenges from adversaries that can only be resolved by way of ever more sophisticated inputs into tactical operations. Lethal Autonomy provides constrained military/security forces with a viable option, but only if implementation has got proper empirically supported foundations. Autonomous weapon systems can be designed and developed to conduct ground, air and naval operations. This monograph offers some insights into the challenges of developing legal, reliable and ethical forms of autonomous weapons, that address the gap between Police or Law Enforcement and Military operations that is growing exponentially small. National adversaries are today in many instances hybrid threats, that manifest criminal and military traits, these often require deployment of hybrid-capability autonomous weapons imbued with the capability to taken on both Military and/or Security objectives. The Westgate Terrorist Attack of 21st September 2013 in the Westlands suburb of Nairobi, Kenya is a very clear manifestation of the hybrid combat scenario that required military response and police investigations against a fighting cell of the Somalia based globally networked Al Shabaab terrorist group.Comment: 52 pages, 6 Figures, over 40 references, reviewed by a reade

Energy Management Systems for Smart Electric Railway Networks: A Methodological Review

Energy shortage is one of the major concerns in today’s world. As a consumer of electrical energy, the electric railway system (ERS), due to trains, stations, and commercial users, intakes an enormous amount of electricity. Increasing greenhouse gases (GHG) and CO2 emissions, in addition, have drawn the regard of world leaders as among the most dangerous threats at present; based on research in this field, the transportation sector contributes significantly to this pollution. Railway Energy Management Systems (REMS) are a modern green solution that not only tackle these problems but also, by implementing REMS, electricity can be sold to the grid market. Researchers have been trying to reduce the daily operational costs of smart railway stations, mitigating power quality issues, considering the traction uncertainties and stochastic behavior of Renewable Energy Resources (RERs) and Energy Storage Systems (ESSs), which has a significant impact on total operational cost. In this context, the first main objective of this article is to take a comprehensive review of the literature on REMS and examine closely all the works that have been carried out in this area, and also the REMS architecture and configurations are clarified as well. The secondary objective of this article is to analyze both traditional and modern methods utilized in REMS and conduct a thorough comparison of them. In order to provide a comprehensive analysis in this field, over 120 publications have been compiled, listed, and categorized. The study highlights the potential of leveraging RERs for cost reduction and sustainability. Evaluating factors including speed, simplicity, efficiency, accuracy, and ability to handle stochastic behavior and constraints, the strengths and limitations of each optimization method are elucidated

Engine on/off control for dimensioning hybrid electric powertrains via convex optimization

This paper presents a novel heuristic method for optimal control of mixed-integer problems that, for given feasible values of the integer variables, are convex in the rest of the variables. The method is based on Pontryagin's maximum principle and allows the problem to be solved using convex optimization techniques. The advantage of this approach is the short computation time for obtaining a solution near the global optimum, which may otherwise need very long computation time when solved by algorithms guaranteeing global optimum, such as dynamic programming (DP). In this paper, the method is applied to the problem of battery dimensioning and power split control of a plug-in hybrid electric vehicle (PHEV), where the only integer variable is the engine on/off control, but the method can be extended to problems with more integer variables. The studied vehicle is a city bus, which is driven along a perfectly known bus line with a fixed charging infrastructure. The bus can charge either at standstill or while driving along a tramline (slide in). The problem is approached in two different scenarios: First, only the optimal power split control is obtained for several fixed battery sizes; and second, both battery size and power split control are optimized simultaneously. Optimizations are performed over four different bus lines and two different battery types, giving solutions that are very close to the global optimum obtained by DP

Vehicle routing and location routing with intermediate stops:A review

This paper reviews the literature on vehicle routing problems and location rout-8 ing problems with intermediate stops. We classify publications into different categories from both an application-based perspective and a methodological perspective. In addition, we analyze the papers with respect to the algorithms and benchmark instances they present. Furthermore, we provide an overview of trends in the literature and identify promising areas for further research.</p