As the world transitions towards sustainable alternatives, transportation electrification emerges as a pivotal strategy within deep decarbonization initiatives undertaken by governments globally. Central to this shift is the role of batteries, specifically those in energy and transportation systems. However, a key challenge often overlooked is the impact of battery aging on the economy and longevity of electric vehicles (EVs). The pressing need to understand and mitigate the costs and implications of battery aging forms the crux of this research. This paper aims to improve the lifecycle economy of EVs participating in energy and transportation systems by factoring in the electrochemical aging modes of the battery. In the first stage, battery electrochemical aging features are modeled by learning cell fading rate under different healthy states from the Stanford experimental dataset. Then, by comprehensively quantifying the impact of depth of discharge, C-rate, state of health, and state of charge, this paper establishes a full lifecycle degradation model to model battery aging under different working conditions and aging stages. In the second stage, battery electrochemical aging features are further integrated into vehicle energy management to realize the effective utilization of BESS in energy and transportation systems. With the proposed energy management scheme, vehicle batteries with different electrochemical aging stages can be flexibly utilized under full lifecycles. The effectiveness of the proposed methodologies is verified under the cases of EVs participating in energy and transportation systems. Results in this paper validate the necessity of factoring battery electrochemical aging features in BESS management and provide a new perspective for further improving the total economy of transportation electrification.