EV Reservation Charging System Using Dynamic Programming
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Solution Overview
Problem
Current electric vehicle charging methods require users to set additional conditions to minimize charging fees, are complex due to varying power source usage and hourly electric fees, and involve excessive calculation, making it difficult to optimize charging power across different hour zones.
Innovation Solution
An electric vehicle reservation charging system that calculates optimal charging power using dynamic programming to minimize fees, independent of power source usage, by determining a preset charging profile based on power rate information and charging constraints, allowing for variable optimal charging power per hour without shifting charging hours or using rapid/slow charging.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If users set additional charging conditions to minimize fees, then charging cost reduction is achieved, but system complexity and user burden increase
Solution Approach 1:
The charging system automatically determines the optimal charging schedule and power distribution without requiring user input or configuration. The controller autonomously analyzes power rate information by hour zone and executes the charging plan, making the system self-serve the fee minimization function without user burden.
Solution Approach 2:
The system pre-calculates the optimal charging schedule by analyzing power rate information before charging begins. By determining the charging profile in advance based on hourly power rates, the system prepares the fee minimization strategy beforehand, eliminating the need for users to set conditions during charging operations.
2Loss of energy
If charging control is performed by selecting hour zones with low electric fees, then charging fee is reduced, but calculation complexity increases excessively
Solution Approach 1:
The charging period is divided into discrete hour zones, each with its own power rate. The system segments the charging schedule into hourly intervals and evaluates each zone independently, transforming a complex continuous optimization problem into a manageable discrete sequence of decisions that can be processed by the ECU.
Solution Approach 2:
The system changes the charging power parameter dynamically according to the hour zone and power rate information. By adjusting the charging power level based on pre-analyzed power rate data for each hour zone, the system achieves fee minimization through parameter adaptation rather than complex real-time calculations.
3Loss of energy
If charging is shifted to hour zones with greatest unused power, then charging fee is minimized, but charging schedule flexibility is reduced
Solution Approach 1:
The charging schedule is made dynamic by allowing variable charging power within each hour zone rather than fixed timing. The system can adjust charging power levels up or down depending on the power rate and battery state, providing flexibility within the structured hour zone framework without requiring rigid schedule shifts.
4Loss of energy
If optimal charging power is calculated by hour using dynamic programming, then charging fee is minimized, but computational resources are increased
Solution Approach 1:
The dynamic programming calculation is segmented into hourly steps, where the charging profile is determined sequentially for each hour zone. This breaks down the complex optimization into manageable discrete stages that can be executed with limited computational resources available in the vehicle's ECU.
Solution Approach 2:
The system changes charging power parameters based on pre-analyzed power rate information for each hour zone. By using the predetermined power rate data to guide power adjustments rather than performing real-time optimization calculations, the system reduces computational power requirements while achieving fee minimization.
Data Source
AI summary
An electric vehicle reservation charging system is provided. The system includes a communication controller that receives charging and discharging reservation setting information and power rate information. A vehicle controller determines a preset charging profile based on an entry of a preset minimum cost charging mode using the charging and discharging reservation setting information and the power rate information. A charging state control is performed based on an optimal charging state profile and an optimal charging power profile that are preset based on the charging profile. A charger then perform a power control for charging or discharging to correspond to a target charging discharging power command determined by the charging state control.