2018-01-5025 Published 13 Jul 20 18 © 2018 SAE International. All Rights Reserved.Design and Analysis of Parallel Hybrid Electric Vehicles for Heavy-Duty Truck Applications in a Total Cost of Ownership Framework Fuyuan Yang  Tsinghua University Chao Xu  State Key Laboratory of Automotive Safety and EnergyJinwei Sun  Tsinghua University Citation: Yang, F., Xu, C., and Sun, J., “Design and Analysis of Parallel Hybrid Electric Vehicles for Heavy-Duty Truck Applications in a Total Cost of Ownership Framework,” SAE Technical Paper 2018-01-5025, 2018, doi:10.4271/2018-01-5025. Abstract Due to the potential on decreasing fuel consumption and design flexibility, parallel configurations are widely used for hybrid electric vehicles (HEVs). However, the fuel economy and economic profitability of parallel HEVs for heavy-duty truck applications under Chinese driving conditions still need to be investigated. It is uneasy to improve the fuel economy of parallel HEVs with a single electric motor from control perspective only. In this article, the battery size of the architecture is optimized by using the dynamic programming (DP) approach, based on a dynamic degradation model of the LiFePO 4 battery. Moreover, based on the DP results, a near-optimal control strategy of the hybrid powertrain system for online applica - tion is proposed. Finally, with two economic assumptions, the initial costs, operation costs, and payback periods are obtained in a total cost of ownership framework perspective. The simulation results show that the fuel consumption can satisfy the Stage 3 fuel consumption standard, which will be implemented in 2021. In addition, more than 18% fuel economy is achieved when compared to that of the conven - tional heavy-duty truck. Under present economic scenarios, the payback period of parallel hybrid electric heavy-duty truck is less than five years. When assumptions are benefited to electrification, the payback period will even be less than three years. Introduction In recent years, environmental concerns and security of energy supply have forced the Chinese government to explore environment-friendly, efficient, and sustainable transportation solutions [ 1]. With high fuel consumption and relatively heavy use in terms of vehicle kilometers traveled, heavy-duty trucks account for nearly 50% of China’s total on-road fuel use [ 2]. Meanwhile, China will implement the Stage 3 fuel consumption standard in 2021 for new heavy commercial vehicles sold in China. Therefore, it is necessary and urgent to investigate the fuel economy potential of hybrid electric vehicles (HEVs) for heavy-duty applications. HEVs are a promising way to reduce fuel consumption and emission in comparison to conventional vehicles. However, there are several major challenges associated with heavy-duty HEVs. Fleet and consumers are more emphasis on economic profitability, and there is a lack of simulation platform to explore and optimize the design of powertrain system and study on the economic impact of hybrid powertrain in different economic scenarios. To overcome these challenges, a model framework including a battery degradation model and a total cost of ownership model is proposed in this article to explore and optimize the powertrain architecture.Optimal design of heavy-duty HEVs is to optimize powertrain architectures and energy management strategies under limit constraints. With the driving cycle known, the largest factor affecting energy management strategy is powertrain configuration. Energy management strategy and design of powertrain should be optimized simultaneously. Comparing with passenger HEVs, heavy-duty HEVs need higher power level components to satisfy heavy load and special driving cycle demand. Four main hybrid powertrain systems, series, parallel, power-split, and series-parallel, have been used in heavy duty vehicles (HDVs) [ 3], as shown in Figure 1 . A basic series hybrid configuration is given in Figure 1a . There is no