ELECTRIC VEHICLE ENERGY MANAGEMENT METHOD BASED ON BEND PREDICTION, TERMINAL DEVICE, AND STORAGE MEDIUM

    公开(公告)号:US20240025422A1

    公开(公告)日:2024-01-25

    申请号:US18254119

    申请日:2021-07-23

    IPC分类号: B60W40/105

    CPC分类号: B60W40/105 B60W2552/30

    摘要: The present disclosure relates to an electric vehicle energy management method based on bend prediction, a terminal device, and a storage medium. The method includes the following steps: S1. counting an average acceleration av of vehicle decelerations; S2. acquiring bend information of a road ahead by an e-horizon system; S3. predicting energy recovery amount during cornering based on the bend information and a maximum cornering speed of a vehicle; and S4. adjusting a logic threshold value for current driving based on the predicted energy recovery amount. With the method of the present disclosure, a supercapacitor can output more energy in advance based on energy likely to be recovered during cornering ahead, so as to free up energy recovery space and to recover energy during cornering, which can reduce power output of a battery, ensure energy recovery, and play a positive role in loss reduction and energy-saving control.

    METHOD FOR CONTROLLING FOLLOWING DISTANCE BASED ON TERRAINS, TERMINAL DEVICE, AND STORAGE MEDIUM

    公开(公告)号:US20240001918A1

    公开(公告)日:2024-01-04

    申请号:US18254112

    申请日:2021-07-23

    IPC分类号: B60W30/16

    CPC分类号: B60W30/16 B60W2552/15

    摘要: The present disclosure relates to a method for controlling a following distance based on terrains, a terminal device, and a storage medium. The method includes the following steps: S1. dynamically acquiring a slope θ of a current driving road; S2. calculating a dynamic following distance d based on the slope θ; S3. determining whether d is within an acceptable following distance range [d1, d2], if d is within the range, controlling the following distance of a vehicle to be d, otherwise proceeding to step S4; and S4. if d is smaller than d1, controlling the following distance of the vehicle to be d1; and if d is greater than d2, controlling the following distance to be d2. With the method of the present disclosure, the following distance can be automatically and dynamically adjusted based on the terrains to achieve the consistency of energy saving and safety.

    LIFT AXLE CONTROL METHOD AND SYSTEM FOR VEHICLE

    公开(公告)号:US20240010284A1

    公开(公告)日:2024-01-11

    申请号:US18247181

    申请日:2021-07-29

    IPC分类号: B62D61/12 B60G17/015

    摘要: Disclosed in the present disclosure are a lift axle control method for a vehicle and a lift axle control system for a vehicle, wherein the method comprises the following steps: step 1) acquiring a load M of the vehicle; step 2) judging whether it needs to lower the lift axle according to the load, and if so, controlling the vehicle to lower the lift axle, and entering into step 3); otherwise, returning to step 1); step 3) calculating an optimal position of lifting the lift axle, controlling the vehicle to lift the lift axle at the optimal position, and entering into step 4); step 4) calculating an optimal position to lower the lift axle, controlling the vehicle to lower the lift axle at the optimal position, and then returning to step 3). The method of the present disclosure can reduce the damage to the road surface and achieve the economy of fuel consumption during running of the vehicle.

    METHOD FOR PREDICTING ENERGY CONSUMPTION-RECOVERY RATIO OF NEW ENERGY VEHICLE, AND ENERGY SAVING CONTROL METHOD AND SYSTEM FOR NEW ENERGY VEHICLE

    公开(公告)号:US20230264578A1

    公开(公告)日:2023-08-24

    申请号:US18020101

    申请日:2021-07-23

    发明人: Yankai TU Junfang LAI

    IPC分类号: B60L50/60 B60L3/12

    摘要: Provided are a method for predicting an energy consumption-recovery ratio of a new energy vehicle, and an energy saving control method and system for the new energy vehicle. The method includes: (1) acquiring, by means of an electronic horizon system, geographic information data of a position that is K meters ahead on a road from a current position of the new energy vehicle; (2) compiling statistics on speed information during the process of the new energy vehicle traveling S meters to reach the current position, values of K and S being the same; and (3) taking the geographic information data and the speed information as input vectors, inputting the same into a trained artificial neural network, and outputting a predicted energy consumption-recovery ratio. The present disclosure can optimize energy control over the vehicle, improve the utilization rate of electrical energy, and increase the traveling mileage.