EV Battery Energy Management via Smart Grid Scheduling
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Solution Overview
Problem
Electric vehicle batteries, particularly lithium-ion batteries, face reduced lifespan and performance due to varying charging environments, cycles, and schemes, necessitating an optimal charging management method that balances battery life with cost-effective charging within smart grid networks.
Innovation Solution
A system that calculates necessary energy based on user schedules and battery characteristics, utilizing a cloud server to collect and analyze user and power network data, setting charging information to optimize battery charging during low electricity sale prices, thereby preventing temporary power network overload and extending battery life.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If batteries are charged during low-fee time bands in smart grid networks, then charging cost is reduced, but temporary overload may occur in the power network
Solution Approach 1:
The energy management device performs preliminary calculations of necessary energy based on user schedules and battery characteristics before charging. It predicts future power network state information and pre-determines optimal charging timing and amounts, preventing concentrated simultaneous charging that causes temporary overload while still achieving cost-effective charging during low-fee periods
Solution Approach 2:
The system continuously receives and processes power network state information feedback, including electricity sale prices and power network load status. This feedback loop enables the energy management device to dynamically adjust charging strategies, balancing cost reduction with power network stability by modifying charging schedules based on real-time network conditions
2Duration of action of stationary object
If batteries are charged with optimal management considering battery characteristics, then battery life and performance are extended, but charging time and complexity increase
Solution Approach 1:
The energy management device automatically performs comprehensive battery management functions including calculating necessary energy based on battery characteristics, determining optimal charging schedules, and executing charging control without requiring complex user intervention. The system self-manages the complexity of monitoring battery state information, analyzing power network conditions, and adjusting charging parameters to extend battery life while maintaining ease of operation for users
Solution Approach 2:
The system pre-calculates necessary energy requirements based on stored battery characteristics and user schedules before charging operations begin. This preliminary preparation allows the system to optimize charging parameters in advance, reducing the complexity of real-time decision-making during actual charging while ensuring optimal battery care
Data Source
AI summary
A system and method for managing energy of an electric vehicle are provided to calculate a necessary amount of energy based on battery characteristics and a user's schedule, and control charging and discharging of the electric vehicle using power information provided by a smart grid. The system includes a cloud server configured to collect a schedule from a user and store and generate the user's schedule information, an energy management device configured to calculate necessary energy based on the received schedule information of the user, set charging information based on power network state information received from a power supplier and the calculated necessary energy, generate a charging request signal based on the set charging information, and store electric energy, and a charging unit configured to transfer the electric energy to the energy management device based on the received charging request signal.