State quantity estimation device, control device, and state quantity estimation method

A method of ECU (Electric Control Unit) of the vehicle which control any devices of a vehicle, which estimates a state quantity that acts on the vehicle and which controls the devices in accordance with the state quantity to moving state to more stably and suitable comprising the steps of:

• storing, in a data storing section, a state quantity that acts on a vehicle and that includes at least a vehicle weight, state covariance that is covariance of the state quantity, and process noise covariance that is covariance of computation noise;
• computing a predictive state quantity from the state quantity and computing, from the state covariance and the process noise covariance, predictive covariance that is covariance of the predictive state quantity;
• obtaining sensor values from a vehicle speed sensor detecting vehicle speed, a longitudinal G sensor detecting acceleration in a longitudinal directing of the vehicle, and a wheel torque sensor estimating torque generated by an engine and applied to wheels of the vehicle, the sensor values being received via a controller area network (CAN);
• computing Kalman gain with use of the sensor values and the predictive covariance;
• computing an estimated state quantity from the Kalman gain, the predictive state quantity, and the sensor values with use of the Kalman filter;
• computing estimated covariance from the Kalman gain, the predictive covariance, and the sensor values with use of the Kalman filter;
• extracting a weight component of the vehicle from the estimated state quantity;
• and
• correcting the process noise covariance by:
• using the weight component of the vehicle;
• and correcting a process noise covariance which was used to estimate a state quantity by referring to a correlation between a state quantity of the vehicle and a process noise covariance;
• writing, in the data storing section, the estimated state quantity as the state quantity, the estimated covariance as the state covariance, the process noise covariance which has been corrected as the process noise covariance,
• wherein the method of ECU uses at least the weight component as the state quantity for controlling suspension devices installed at a left-front position, a right-front position, a left-rear position, and a right-rear position of the vehicle to adjust damping forces of the suspension devices, resulting in improved vehicle stability during acceleration, braking, and concerning,
• wherein, in the method of ECU, the weight component which has been extracted is output as a current weight of the vehicle,
• wherein the method of ECU computes an average and a standard deviation of weight components of the vehicle,
• wherein:
• the state quantity further includes a slope component of a road surface on which the vehicle moves;
• the process noise covariance includes at least vehicle weight noise in estimation of the vehicle weight and slope component noise in estimation of the slope component;
• and
• the method of ECU corrects the process noise covariance so that the vehicle weight noise is directly or indirectly proportional to the standard deviation of the vehicle weight.

ECU (Electronic Control Unit) for vehicle which estimates a state quantity which acts on a device of a vehicle which is for controls to more stably and suitably moving state of the vehicle comprising:

• a data storing section in which a state quantity that acts on a vehicle and that includes at least a vehicle weight, state covariance that is covariance of the state quantity, and process noise covariance that is covariance of computation noise are stored;
• a predictive quantity computing section which computes a predictive state quantity from the state quantity and which computes, from the state covariance and the process noise covariance, predictive covariance that is covariance of the predictive state quantity;
• an obtaining section which obtains sensor values from a vehicle speed sensor detecting vehicle speed, a longitudinal G sensor detecting acceleration in a longitudinal direction of the vehicle, and a wheel torque sensor estimating torque generated by an engine and applied to wheels of the vehicle, the sensor values being received via a controller area network (CAN);
• a Kalman gain computing section which computes Kalman gain with use of the sensor values and the predictive covariance;
• an estimated quantity computing section which computes an estimated state quantity from the Kalman gain, the predictive state quantity, and the sensor values with use of the Kalman filter and which computes estimated covariance from the Kalman gain, the predictive covariance, and the sensor values with use of the Kalman filter;
• a weight component extracting section which extracts a weight component of the vehicle from the estimated state quantity;
• and
• a process noise covariance correcting section which corrects the process noise covariance by:
• using the weight component which has been extracted by the weight component extracting section;
• and correcting a process noise covariance which was used to estimate a state quantity by referring to a correlation between a state quantity of the vehicle and a process noise covariance,
• the estimated state quantity being written as the state quantity in the data storing section, the estimated covariance being written as the state covariance in the data storing section, the process noise covariance which has been corrected being written as the process noise covariance in the data storing section,
• wherein the ECU uses at least the weight component as the state quantity for controlling suspension devices installed at a left-front position, a right-front position, a left-rear position, and a right-rear position of the vehicle to adjust damping forces of the suspension devices, resulting in improved vehicle stability during acceleration, braking, and cornering,
• wherein the weight component extracting section computes an average and a standard deviation of weight components of the vehicle,
• wherein the weight component extracting section includes a weight determining section which determines the weight component in accordance with information indicative of one or more selected from the group consisting of the number of computations of the estimated state quantity and a value of the standard deviation, and
• wherein:
• the weight component extracting section further includes a stability flag which is initially set to OFF;
• the group from which the one or more are selected in the weight determining section further includes ON/OFF of the stability flag;
• and
• the weight determining section
• determines, as the weight component which has been extracted, the weight component which has been most recently extracted, in a case where the number of computations of the estimated state quantity is equal to or lower than a predetermined number,
• determines the average as the weight component which has been extracted, and sets the stability flag to ON, in a case where the number of computations of the estimated state quantity exceeds the predetermined number and the standard deviation is lower than a predetermined threshold,
• determines, as the weight component which has been extracted, the weight component which was extracted in an immediately previous computation or any of computations before the immediately previous computation in which the stability flag was set to ON, in a case where (i) the stability flag is ON, (ii) the number of computations of the estimated state quantity exceeds the predetermined number, and (iii) the standard deviation is equal to or higher than the predetermined threshold, and
• determines, as the weight component which has been extracted, the weight component which has been most recently extracted, in a case where (i) the number of computations of the estimated state quantity exceeds the predetermined number, (ii) the standard deviation is equal to or higher than the predetermined threshold, and (iii) the stability flag is OFF.