Integrating battery degradation in a cost of ownership framework for hybrid electric vehicle design optimization

Abstract

Prior design optimization efforts do not capture the impact of battery degradation and replacement on the total cost of ownership, even though the battery is the most expensive and least robust powertrain component. A novel, comprehensive framework is presented for model-based parametric optimization of hybrid electric vehicle powertrains, while accounting for the degradation of the electric battery and its impact on fuel consumption and battery replacement. This is achieved by integrating a powertrain simulation model, an electrochemical battery model capable of predicting degradation, and a lifecycle economic analysis (including net present value, payback period, and internal rate of return). An example design study is presented here to optimize the sizing of the electric motor and battery pack for the North American transit bus application. The results show that the optimal design parameters depend on the metric of interest (i.e. net present value, payback period, etc.). Finally, it is also observed that the fuel consumption increases by up to 10% from “day 1” to the end of battery life. These results highlight the utility of the proposed framework in enabling better design decisions as compared to methods that do not capture the evolution of vehicle performance and fuel consumption as the battery degrades.

Evaluating emissions and sensitivity of economic gains for series plug-in hybrid electric vehicle powertrains for transit bus applications

“…Design space exploration for series and parallel architecture powertrains of MD truck and transit bus PHEVs was performed by the authors in previous studies. 31–33 The processes and results described in the present paper are based on, and an extension of, the work performed in previous studies. 31–33 The flowchart shown in Figure 1 shows how the results from Hoshing et al, 32 and Vora et al 33 have been used in the present paper.…”

Accelerated battery lifetime simulations using adaptive inter-cycle extrapolation algorithm

“…Equation ( 14) encodes the degradation that occurs over each cycle into a continuous-time framework that can then be solved by standard numerical integrators. In this context, the fixed-step 'extrapolation' method [22,23,24,25] is the Forward Euler solution. We improve on this by using an adaptive numerical method [39,40].…”

“…This algorithm was first proposed for fuel cell models by Mayur et al [22,23] as the 'time-upscaling method', and adapted to lithium-ion batteries by Kupper et al [24]. Independently, Vora et al [25] proposed a similar algorithm and called it 'extrapolation'. This fixed-size linear extrapolation algorithm has two major downsides, and has not gained wide-spread traction so far.…”

The service task of automotive troubleshooting process in collaborative environment using knowledge support approach

“…As the previous researches 9–13 proposed, product lifecycle management (PLM) provides cooperative approaches toward product-oriented settings in industry. It offers a communicated framework for participants by using a suite of technologies and tools.…”