Fast Optimal Energy Management with Engine On/Off Decisions for Plug-in Hybrid Electric Vehicles

In this paper we demonstrate a novel alternating direction method of multipliers (ADMM) algorithm for the solution of the hybrid vehicle energy management problem considering both power split and engine on/off decisions. The solution of a convex relaxation of the problem is used to initialize the optimization, which is necessarily nonconvex, and whilst only local convergence can be guaranteed, it is demonstrated that the algorithm will terminate with the optimal power split for the given engine switching sequence. The algorithm is compared in simulation against a charge-depleting/charge-sustaining (CDCS) strategy and dynamic programming (DP) using real world driver behaviour data, and it is demonstrated that the algorithm achieves 90\% of the fuel savings obtained using DP with a 3000-fold reduction in computational time

Parallel ADMM for robust quadratic optimal resource allocation problems

An alternating direction method of multipliers (ADMM) solver is described for optimal resource allocation problems with separable convex quadratic costs and constraints and linear coupling constraints. We describe a parallel implementation of the solver on a graphics processing unit (GPU) using a bespoke quartic function minimizer. An application to robust optimal energy management in hybrid electric vehicles is described, and the results of numerical simulations comparing the computation times of the parallel GPU implementation with those of an equivalent serial implementation are presented

An ADMM Algorithm for MPC-based Energy Management in Hybrid Electric Vehicles with Nonlinear Losses

In this paper we present a convex formulation of the Model Predictive Control (MPC) optimisation for energy management in hybrid electric vehicles, and an Alternating Direction Method of Multipliers (ADMM) algorithm for its solution. We develop a new proof of convexity for the problem that allows the nonlinear dynamics to be modelled as a linear system, then demonstrate the performance of ADMM in comparison with Dynamic Programming (DP) through simulation. The results demonstrate up to two orders of magnitude improvement in solution time for comparable accuracy against DP

Optimal Power Allocation in Battery/Supercapacitor Electric Vehicles using Convex Optimization

This paper presents a framework for optimizing the power allocation between a battery and supercapacitor in an electric vehicle energy storage system. A convex optimal control formulation is proposed that minimizes total energy consumption whilst enforcing hard constraints on power output and total energy stored in the battery and supercapacitor. An alternating direction method of multipliers (ADMM) algorithm is proposed, for which the computational and memory requirements scale linearly with the length of the prediction horizon (and can be reduced using parallel processing). The optimal controller is compared with a low-pass filter against an all-battery baseline in numerical simulations, where it is shown to provide significant improvement in battery degradation (inferred through reductions of 71.4% in peak battery power, 21.0% in root-mean-squared battery power, and 13.7% in battery throughput), and a reduction of 5.7% in energy consumption. It is also shown that the ADMM algorithm can solve the optimization problem in a fraction of a second for prediction horizons of more than 15 minutes, and is therefore a promising candidate for online receding-horizon control

P1_7 Row, Let's Row Away

This paper investigates the potential, energy difference between flying to a destination, compared to rowing to it. i.e. the energy burned per passenger on an airplane, compared to a passenger rowing across the sea to the destination. The destinations we consider are from London Heathrow to New York JFK airport, and we found that for a Boeing 747 and an Airbus A380, the energy used is 6069.1 MJ and 5677.8 MJ respectively. The amount of energy to row the distance in a single lightweight scull was found to be 128.67 MJ; in comparison to the Airbus the rower uses approximately 98% less energy

P1_6 Geothermal Power

Geothermal power is a green power source that could provide substantial renewable power. This paper looks at the approximate energy that the planet could provide using the stored thermal energy beneath the surface of the Earth. It was calculated that the energy that could be used was 3.9x1030J. However, actually extracting this energy is unrealistic with today’s technology, as well as hazardous to the planet

P1_2 Melting Mirrors

High powered lasers have been portrayed as being able to cut through almost anything, but a simple mirror seems to easily reflect them. The purpose of a mirror is to reflect optical light but surely there is a limit to the energy it can do so before it begins to deform and melt. Thorough research into this showed us that if we consider a mirror with an optical coating of silver and a 500 nm laser was applied to it, it would take 11.65 J to destroy the illuminated area, if conductivity and scattering were not considered

P1_10 Fus Ro Dah

The power of the “Thu’um†is unquestionable within the video game, Skyrim [1]. This paper investigates the possibility of knocking down an opponent using only their voice. It was calculated that the minimum amount of force required to do so is 121.2N, and that an average person can only produce 3.74N