DE102021104523B3 - land vehicle - Google Patents

Abstract

The invention relates to a land vehicle (5) which is set up to be driven by the muscular power of a driver and has a motor (9) which is set up to drive the land vehicle (5), the land vehicle (5) having an effort measuring device (6 ) which is set up to measure an effort A(t) of the driver caused by the application of muscle power, a speed measuring device (7) which is set up to determine a speed v(t) of the land vehicle (5), and a control unit ( 8) which is set up to control the motor (9) and to determine a plurality of different driving situations of the land vehicle (5) on the basis of the measured effort A(t) and the measured speed v(t), one of the driving situations being a starting situation (1) and t is the time, and when the driving situation is determined as the starting situation (1), to control a support level u(t) of the motor (9) with a value ustart(t). .

Description

The invention relates to a land vehicle.

Conventional land vehicles exist that can be propelled by both human power of a driver and an engine. An example of such a land vehicle is an electric bicycle, which can be a pedelec in particular. The land vehicles usually have a control unit that controls the power released by the engine to propel the land vehicle. Conventional control units have the problem that they do not adapt the power of the engine, or do not do so quickly enough, in the event of abrupt changes in the driver's effort. An example of such an abrupt change in effort is when the driver has to exert more effort at the beginning of a hill. Here it would be desirable if the power of the engine was increased. Conversely, it would be desirable for the power of the engine to be reduced quickly when driving downhill, so that the land vehicle is traveling at too high a speed and the associated increased risk of accidents is avoided. Another example would be the launch of the land vehicle. Here it would be particularly desirable that when the land vehicle is started, the engine should give strong support to the start, for example to avoid the driver of the electric bicycle swaying during the start, which can be potentially dangerous for the driver.

DE 602 23 307 T2 discloses a control device for a bicycle with an auxiliary motor. U.S. 5,853,062 A describes an electrically assisted recumbent bicycle. JP 2020 - 40 503 A discloses an electric bicycle and a method for controlling the electric bicycle. EP 2 377 713 A1 discloses an electrically powered bicycle. EP 2 848 514 A1 discloses an electrically powered bicycle.

It is therefore an object of the invention to provide a land vehicle which is drivable by both human power of a driver and an engine and has a controller for the engine which responds quickly to abrupt changes in driver effort. The object is solved by each of claims 1, 4, 6 and 7.

The land vehicle according to the invention is set up to be driven by the muscular power of a driver and has a motor that is set up to drive the land vehicle, the land vehicle having an effort measuring device that is set up to measure an effort A(t) des caused by the application of muscle power driver, a speed measuring device that is set up to determine a speed v(t) of the land vehicle, and a control unit that is set up to control the engine and based on the measured effort A(t) and the measured speed v( t) to determine a plurality of different driving situations of the land vehicle, one of the driving situations being a starting situation and t being the time, and, if the driving situation is determined as the starting situation, a support level u(t) of the motor with a value u _start ( t), i.e. u(t)=u _start (t).

The starting situation can be determined particularly reliably and particularly quickly on the basis of the measured speed and the measured exertion. As soon as the starting situation is recognized, the support level u(t)=u _start (t) is set. u _start (t) can now be selected in such a way that sufficient support is provided by the engine in the starting situation of the land vehicle.

The motor can be an electric motor, for example, and the land vehicle can have a battery that is set up to supply the electric motor with electrical energy.

The support level u(t) can be positive, whereby the engine drives the land vehicle, and/or negative, whereby the engine brakes the land vehicle. An example of the motor that is set up to drive and brake the land vehicle is the electric motor that is set up to carry out recuperation. For a particularly sensitive control of the motor, it is preferred that the control unit is set up to control the assistance level u(t) in small increments. For example, the increments can be a maximum of 3%, in particular a maximum of 1.5% or a maximum of 1%. The maximum range of the assistance level u(t) can be from 0% to 100% or, in the case that the engine is also set up to brake the land vehicle, from -100% to 100%.

The speed measuring device can be set up, for example, to determine the speed v(t) from the speed of a wheel of the land vehicle, in particular a wheel of an electric bicycle, and the diameter of the wheel.

According to the invention, the effort A(t) is a mechanical power P(t), in particular a pedaling power, of the driver, ie A(t)=P(t), and the control unit is set up to query in a first query whether v(t)<S _v and P(t)<S _P , and in case the answer is yes, to determine the driving situation as the starting situation, where S _V is a speed threshold value and S _P are a performance threshold. It was found that the starting situation can be reliably determined based on the first query.

To determine the power P(t), the effort measuring device can have a torque sensor that is set up to measure a torque generated by the driver during the effort A(t) and an angular velocity sensor that is set up to measure an angular velocity associated with the torque measure up. The angular velocity can be a speed, for example. The power P(t) can then be determined as the product of the torque and the angular velocity.

The speed threshold value S _P can be, for example, from 5 km/h to 12 km/h, with low speeds being more suitable for those drivers who are untrained and high speeds being more suitable for those drivers who are well trained. The power threshold S _P can be, for example, from 30 watts to 120 watts. Lower powers, such as from 30 watts to 75 watts, are more suitable when the land vehicle is a light electric bicycle. High powers, such as from 50 watts to 120 watts, are more appropriate when the land vehicle is a heavy electric bicycle, such as a mountain bike, or has more than two wheels. It also applies here that rather low values from the respective areas are suitable for those drivers who are untrained, and rather high values from the respective areas are suitable for those drivers who are well trained.

It is preferred that the control unit is set up, in the event that the answer to the first query is no, to query in a second query whether v(t)<S _V +C _V and P(t)<S _P + C _P and (v(t)-v(t-τ _V ) )/τ _V <S _DV , and in the case that the answer to the second query is yes, to determine the driving situation as the starting situation, where Cv is a positive constant, CP is a positive constant, τ _v is a deceleration, and _{S DV} is a negative acceleration threshold. The second query describes a situation in which the starting situation lasts longer and is associated with problems that lead to a drop in velocity v(t). This allows the starting situation to be determined particularly quickly and reliably. The constants _CV and _CP allow higher speed and higher performance than in the first query. Cv depends on the type of land vehicle. For example, Cv can be from 1 km/h to 3 km/h, where Cv=2 km/h is suitable for most electric bicycles. For example, C _P can be from 0 to 50 watts, with the constant C _P being from 10 watts to 20 watts suitable for most electric bicycles. For example, the acceleration threshold S _DV can be from -1 km/(h*s) to -3 km/(h*s), where S _DV =-2 km/(h*s) for most drivers and routes that use this Land vehicle travels, is suitable. The delay τ _v can be, for example, from 1 s to 3 s. The more noise is expected in the measurement of the velocity v(t), the longer the delay τ _V should be selected. τ _v =2 s is suitable for most cases of noise.

According to the invention, the driving situations have a stable situation, an uphill situation and a downhill situation, with the control unit being set up, when the driving situation is determined as the stable situation, to control the assistance level u(t) with a value u _stable (t), i.e u(t)=u _stable (t), when the driving situation is determined as the uphill situation, to control the assistance level u(t) with a value u _on (t), i.e. u(t)=u _on (t), and, when the driving situation is determined as the downhill situation, to control the assist level u(t) with a value u _ab (t), that is, u(t)=u _ab (t). By providing the uphill situation and the associated support level u _to (t), the motor can quickly support the driver at the beginning of an incline. By providing the downhill situation and the support level u _ab (t) associated with it, it can be avoided that the motor provides too much support when driving downhill, as a result of which an excessive speed and the associated risk of an accident can be avoided. By providing the stable situation and the support level u _stable (t) associated with it, all those driving situations that are not the starting situation, the uphill situation or the downhill situation can be covered.

u _start (t), u _stable (t), u _up (t) and u _down (t) are preferably constants, i.e. u _start (t)=u _1,start , u _stable (t)=u _1,stable , u _up (t)=u _1,up and u _down (t)=u _1,down . It can be the case that u _1,start ≥ u _1,auf ≥ u _1,stabil ≥ U _1,ab or that u _1,auf ≥ u _1,start ≥ u _1,stabil ≥ u _1,ab . It is preferred that u _1,start is from -5% to 100%, or from 0% to 100%, or from 10% to 100%. It is preferred that u is _1.0 from -5% to 100%, or from 0% to 100%, or from 10% to 100%. It is preferred that u _1,stable is from - 50% to 50% or from 0% to 50%. It is preferred that u is _1,ab from -100% to 5% or from 0% to 5%.

According to the invention, the control unit is set up to query whether D(t )>S _D1 *dD(t) and in case the answer is yes, determining the driving situation as the uphill situation, where τ a sampling time of the control unit, D(t) a force applied by the driver at his effort A(t) to a driving wheel of the land vehicle, which is in particular a rotational force, S _D1 a constant and dD(t) a unit-less force gradient of the force over time D(t) determined in particular according to dD(t) = 1-k _D *(D(t)-D(t-τ _D ))/τ _D , where k _D is a constant and τ _D is a delay . The uphill situation can be reliably determined by this query if the driving situation was determined as the stable situation or as the starting situation at time t−τ. By using the force gradient dD(t), it is advantageously not necessary to determine the inclination of the land vehicle, for example by means of an inclination sensor, to determine the uphill situation. τ can be from 0.1 s to 2 s, in particular 1 s. S _D1 depends on the aerodynamics of the land vehicle. For example, S _D1 can be determined by the formula 0.07*M, where M is the sum of the masses of the driver and the land vehicle in kg and S _D1 is given in N. For example, for an electric bicycle as the land vehicle, S _D1 can be from 3.5 N to 14 N, which corresponds to M from 50 kg to 200 kg. k _D can be, for example, from 0.1 s/N to 0.5 s/N. τ _D can be, for example, from 2 s to 5 s. The rotational force D(t) is directed in the tangential direction of the drive wheel and can act on the outer end in the radial direction of the drive wheel.

According to the invention, the control unit is set up to query whether D(t)>S _D1 * in the event that the driving situation is not determined as the starting situation and that at a time t-τ the driving situation was determined as the uphill situation. dD(t)-H _D and in case the answer is yes, determining the driving situation as the uphill situation, where D(t) is a force applied by the driver at his effort A(t) to a driving wheel of the land vehicle , specifically a torque, dD(t)=1-k _D *(D(t)-D(t-τ _D ))/τ _D , S _D1 a constant, H _D a constant, k _D a constant, τ a sampling time of the control unit and τ _D are a delay. The uphill situation can be reliably determined by this query if the driving situation was also determined as the uphill situation at time t−τ. By using the force gradient dD(t), it is advantageously not necessary to determine the inclination of the land vehicle, for example by means of an inclination sensor, to determine the uphill situation. τ can be from 0.1 s to 2 s, in particular 1 s. S _D1 depends on the aerodynamics of the land vehicle. For example, S _D1 can be determined by the formula 0.07*M, where M is the sum of the masses of the driver and the land vehicle in kg and S _D1 is given in N. For example, for an electric bicycle as the land vehicle, S _D1 can be from 3.5 N to 14 N, which corresponds to M from 50 kg to 200 kg. k _D can be, for example, from 0.1 s/N to 0.5 s/N. τ _D can be, for example, from 2 s to 5 s. H _D depends on the terrain on which the land vehicle is traveling. The hillier the terrain, the higher H _D should be selected. For example, HD can be from 0.1N to 2N, where it has been found that _HD = _0.5N is suitable for most terrain. The rotational force D(t) is directed in the tangential direction of the drive wheel and can act on the outer end in the radial direction of the drive wheel.

According to the invention, the control unit is set up, in the event that the driving situation is not determined as the starting situation and that at a point in time t-τ the driving situation was determined as the stable situation, as the starting situation or as the downhill situation, to query whether D(t)<S _D2 *dD(t) and in case the answer is yes, to determine the driving situation as the downhill situation, where τ a sampling time of the control unit, D(t) one of the driver at its Effort A(t) force applied to a drive wheel of the land vehicle, which is in particular a rotational force, S _D2 is a constant and dD(t) is a unitless force gradient over time of the force D(t) which is in particular according to dD(t)=1- k _D *(D(t)-D(t-τ _D ))/τ _D , where k _D is a constant and τ _{d is} a delay. The downhill situation can be reliably determined by this query. By using the force gradient dD(t), it is advantageously not necessary to determine the inclination of the land vehicle, for example by means of an inclination sensor, to determine the downhill situation. τ can be from 0.1 s to 2 s, in particular 1 s. S _D2 depends on the aerodynamics of the land vehicle. For example, S _D2 can be determined by S _D2 =3.65N if M≤85 kg and S _D2 =4.5N-0.01*M*N/kg if M>85 kg, where M is the sum the masses of the driver and the ground vehicle in kg. For example, for an electric bicycle as the land vehicle, S _D2 can be from 3.65 N to 2.5 N, which corresponds to M from 50 kg to 200 kg. k _D can be, for example, from 0.1 s/N to 0.5 s/N. τ _D can be, for example, from 2 s to 5 s. The rotational force D(t) can be directed in the tangential direction of the drive wheel and can act on the end lying on the outside in the radial direction of the drive wheel.

The control unit is preferably set up to determine the driving situation as the stable situation in the case that the driving situation is not determined as the starting situation, the uphill situation or the downhill situation. As a result, the control unit is set up to determine precisely four different driving situations.

The control unit is preferably set up by the engine for driving the land to control the motor power P _M (t) provided by the vehicle as a function of the support level u(t) and the power P(t) of the driver. This is the case, for example, when the land vehicle is a pedelec. For example, the control unit can be set up to determine the engine power according to P _M (t)=u(t)*K*P(t). The factor K indicates the maximum possible motor support. K can be, for example, from 1 to 5 and is in particular 3.

It is preferred that the land vehicle has a body sensor that is set up to measure physiological data PD(t) of the driver's body and a computing unit that is set up to create a prognosis mPD(t+T) of the physiological data, wherein the control unit is set up to provide a predetermined reference variable for the physiological data PD(t), to take the prognosis mPD(t+T) as a controlled variable and to select a support level u ₂ (t) of the motor as a manipulated variable, wherein the control unit is set up to select a predetermined constant u _1,start for u _start (t) if u _1,start >u ₂ (t), or to select u ₂ (t) for u _start (t) if u ₂ (t)>u _1,start . In summary, the following applies: u _start (t)=max[u _1,start , u ₂ (t)]. Alternatively, it is preferred that the land vehicle has a body sensor that is set up to measure physiological data PD(t) of the driver's body and a computing unit that is set up to create a prognosis mPD(t+T) of the physiological data , wherein the control unit is set up to provide a predetermined reference variable for the physiological data PD(t), to take the prognosis mPD(t+T) as a controlled variable and to select a support level u ₂ (t) of the motor as a manipulated variable, wherein the control unit is set up to select a predetermined constant u _1,start for Ustart (t) if u _1,start >u ₂ (t), or to select u ₂ (t) for u _start (t) if u ₂ (t)>u _1,start , - to select a predetermined constant u _1, stabil for u _stable (t) if u _1,stabil >u ₂ (t), or for u _stable (t) u ₂ (t ) to choose if u ₂ (t)>u _1,stable , - for u _on (t) a predetermined constant u _1,on to choose if u _{1, on} >u ₂ (t), or for u _on (t) to choose u ₂ (t) if u ₂ (t)>u _1, ab , and - for u _ab (t) to choose a predetermined constant u _1,ab if u _1,ab >u ₂ ( t)-u _korr , or to be chosen for u _ab (t) u ₂ (t) -u _korr if u ₂ (t)-u _korr >u _1,ab , where U korr is a positive constant. u _korr depends on the land vehicle and the engine. What is achieved in both cases is that a control, in which the different driving situations are determined, is combined with a regulation of the driver's physiological data. By using the land vehicle as the control variable the prognosis mPD(t+T), in which the time t+T is the delay T in the future, the control unit can react to changes in load much more quickly than it would if than the controlled variable the physiological data PD(t) would be taken. As a result, control deviations of the controlled variable from the reference variable can be kept much lower than would be the case if the physiological data PD(t) were taken as the controlled variable. The appropriate reference variable for the physiological data PD(t) can now be specified for each driver, it being conceivable that the reference variable varies over time. For example, a sports doctor or a physiotherapist can be used to set the reference variable. u _korr depends on the land vehicle and the engine. u _korr can be from 1% to 50% and in particular for an electric bicycle from 3% to 5%.

gespeichert ist, in dem $$B_1\left(t\right)={\displaystyle \sum _{i=1}^j{a}_{1i}\ast \left({\displaystyle \sum _{d=0}^{D_i}A\left(t-{\tau }_{1i}-d\ast K_i\right)/\left(D_i+1\right)}\right)}$$

und $$B_2\left(t\right)={\displaystyle \sum _{i=1}^k{a}_{2i}\ast PD\left(t-{\tau }_{2i}\right)}$$

ist, wobei die Recheneinheit eingerichtet ist, mittels eines Optimierungsalgorithmus die Koeffizienten a_xi, den Summanden a₁₀, die Verzögerungen τ_xi zumindest teilweise und die Verzögerung T für jeden Fahrer individuell so anzupassen, dass mPD(t+T) die gemessenen physiologischen Daten PD(t+T) annähert und anhand des Modells die Prognose mPD(t+T) der physiologischen Daten PD(t+T) zu erstellen. j kann beispielsweise aus dem Bereich von 2 bis 5 ausgewählt sein. k kann beispielsweise aus dem Bereich von 1 bis 4 ausgewählt sein. In dem Term B₁(t) wird eine Mittelung von Di+1 Messpunkten vorgenommen, die einen Zeitabstand K_i haben. Beispielsweise können die Werte für Di aus einem Bereich von 0 bis 60 ausgewählt sein. Die Werte für den Zeitabstand K_i können beispielsweise aus einem Bereich von 0,2 s bis 2 s ausgewählt sein. Dadurch, dass die Recheneinheit eingerichtet ist, die Koeffizienten a_xi, den Summanden a₁₀, die Verzögerungen τ_xi und die Verzögerung T für jeden Fahrer individuell anzupassen, können die Regelabweichungen für jeden beliebigen Fahrer niedrig gehalten werden. Verschiedene Fahrer reagieren unterschiedlich schnell auf eine Änderung einer von außen auf den Fahrer wirkenden Belastung. Ist der Fahrer eher untrainiert, so wird sie eher langsam auf die Änderung reagieren, ist der Fahrer eher trainiert, so wird sie eher schnell auf die Änderung reagieren. Indem die Recheneinheit nicht nur eingerichtet ist, die Koeffizienten a_xi und den Summanden a₁₀ sondern auch die Verzögerungen τ_xi und die Verzögerung T für jeden Fahrer individuell anzupassen, kann das Modell widerspiegeln, dass verschiedene Fahrer unterschiedlich schnell auf die Änderungen der Belastung reagieren. Dadurch hat die Prognose für jeden Fahrer eine besonders hohe Genauigkeit, wodurch auch Regelungsabweichungen besonders niedrig sind. Dadurch, dass die Regelungsabweichungen besonders niedrig sind, ist es nun möglich, das Landfahrzeug so zu steuern, dass Überanstrengungen des Fahrers vermieden werden dass gleichzeitig eine Unterstützung durch den Motor möglichst gering ist, um einen möglichst geringen Energieverbrauch zu erreichen, und/oder um zu erreichen, dass der Fahrer sich ausreichend anstrengt, damit eine Fitness des Fahrers verbessert wird.It is preferred that in the computing unit a mathematical model of the form $$mPD\left(t+T\right)=a_{10}+{\displaystyle \sum _x{B}_x\left(t\right)}$$

is stored in which $$B_1\left(t\right)={\displaystyle \sum _{i=1}^j{a}_{1i}\ast \left({\displaystyle \sum _{\mathrm{i.e}=0}^{D_i}A\left(t-{\tau }_{1i}-\mathrm{i.e}\ast K_i\right)/\left(D_i+1\right)}\right)}$$

and $$B_2\left(t\right)={\displaystyle \sum _{i=1}^k{a}_{2i}\ast PD\left(t-{\tau }_{2i}\right)}$$

is set up, by means of an optimization algorithm, the coefficients a _xi , the summand a ₁₀ , the delays τ _xi , at least in part, and the delay T for each driver are individually adjusted in such a way that mPD(t+T) corresponds to the measured physiological data PD (t+T) and to use the model to create the prognosis mPD(t+T) of the physiological data PD(t+T). j can be selected from the range of 2 to 5, for example. k can be selected from the range of 1 to 4, for example. In the term B ₁ (t), an averaging of Di+1 measuring points is carried out, which have a time interval K _i . For example, the values for Di can be selected from a range of 0-60. The values for the time interval K _i can be selected from a range of 0.2 s to 2 s, for example. Since the computing unit is set up to adapt the coefficients a _xi , the summand a ₁₀ , the delays τ _xi and the delay T individually for each driver, the system deviations for any driver can be kept low. Different drivers react at different speeds to a change in a load acting on the driver from the outside. If the driver is rather untrained, it will react rather slowly to the change, if the driver is rather trained, it will react rather quickly to the change. By not only setting up the arithmetic unit, the Koef ficiant a _xi and the summand a ₁₀ but also the deceleration τ _xi and the deceleration T for each driver individually, the model can reflect that different drivers react at different speeds to the changes in the load. As a result, the prognosis for each driver has a particularly high degree of accuracy, which means that control deviations are also particularly low. Due to the fact that the control deviations are particularly low, it is now possible to control the land vehicle in such a way that overexertion on the part of the driver is avoided, that at the same time support from the motor is as low as possible in order to achieve the lowest possible energy consumption and/or to achieve that the driver exerts enough effort so that a fitness of the driver is improved.

The physiological data PD(t) preferably include a heart rate, a heart rate variability, an electrocardiogram, an oxygen saturation of the blood, a blood pressure, and/or a neurological activity, in particular an electroencephalography.

ist. 1 kann beispielsweise aus dem Bereich von 1 bis 4 ausgewählt sein. Es ist bevorzugt, dass das Landfahrzeug einen Temperatursensor aufweist, der eingerichtet ist, die Temperatur Temp(t) in der Umgebung des Landfahrzeugs zu messen, und in dem Modell $$B_4\left(t\right)={\displaystyle \sum _{i=1}^m{a}_{4i}\ast Temp\left(t-{\tau }_{4i}\right)}$$

ist. m kann beispielsweise aus dem Bereich von 1 bis 2 ausgewählt sein. Es ist bevorzugt, dass das Landfahrzeug einen Neigungssensor aufweist, der eingerichtet ist, eine Neigung N(t) des Landfahrzeuas zu messen, und in dem Modell $$B_5\left(t\right)={\displaystyle \sum _{i=1}^n{a}_{5i}\ast N\left(t-{\tau }_{5i}\right)}$$

ist. n kann beispielsweise aus dem Bereich von 1 bis 4 ausgewählt sein. Durch Vorsehen einer oder mehrere der Terme B₃(t), B₄(t) und B₅(t) kann die Genauigkeit der Prognose erhöht werden.It is preferred that the land vehicle has an altimeter arranged to measure the height H(t) of the land vehicle and in the model $$B_3\left(t\right)={\displaystyle \sum _{i=1}^l{a}_{3i}\ast H\left(t-{\tau }_{3i}\right)}$$

is. 1 can be selected from the range of 1 to 4, for example. It is preferred that the land vehicle has a temperature sensor that is set up to measure the temperature Temp(t) in the area surrounding the land vehicle and in the model $$B_4\left(t\right)={\displaystyle \sum _{i=1}^m{a}_{4i}\ast Temp\left(t-{\tau }_{4i}\right)}$$

is. m can be selected from the range of 1 to 2, for example. It is preferred that the land vehicle has an inclination sensor which is set up to measure an inclination N(t) of the land vehicle and in the model $$B_5\left(t\right)={\displaystyle \sum _{i=1}^n{a}_{5i}\ast N\left(t-{\tau }_{5i}\right)}$$

is. n can be selected from the range of 1 to 4, for example. The accuracy of the forecast can be increased by providing one or more of the terms B ₃ (t), B ₄ (t) and B ₅ (t).

zu bestimmen, wobei K_P, K_I und K_D Regelparameter sind, wobei e(t) die Regelungsabweichung zum Zeitpunkt t ist, wobei die Funktionen f₁(e), f₂(e) und f₃(e) so gewählt sind, dass Unterschätzungsfehler stärker als Überschätzungsfehler gewichtet werden. Dadurch werden Abweichungen der Regelgröße zu größeren Werten als die Führungsgröße weniger wahrscheinlich als Abweichungen der Regelgröße zu niedrigen Werten als die Führungsgröße. Dadurch können die Überanstrengungen vermieden werden, die einen körperlichen Schaden des Fahrers verursachen können. Es ist besonders bevorzugt, dass $${ƒ}_1\left(e\right)={\displaystyle \sum _{i=0}^p{c}_{i1}\ast e^i}$$

und $${ƒ}_2\left(e\right)={\displaystyle \sum _{i=0}^q{c}_{i2}\ast e^i}$$

und f₃(e) = 0 für e < 0 sowie f₃(e) = e für e ≥ 0 ist, wobei in f₁(e) und f₂(e) das Polynom in verschiedenen Bereichen von e verschieden sein kann. Beispielsweise können die Funktionen f₁(e) und f₂(e) eine Winkelhalbierende aufweisen und lediglich in einem Bereich 0<e<E₁ beziehungsweise 0<e<E₂ oberhalb der Winkelhalbierenden liegen. Beispielsweise kann, insbesondere wenn es sich bei den physiologischen Daten um eine Herzfrequenz handelt, gelten: f₁(e)=f₂(e)=e für e>12 oder e<0 und f₁(e)=f₂(e)=2*e-0,082*e² für 0≤e≤12. Für f₃(e) kann beispielsweise gelten: f₃(e)=e für e>0 und f₃(e)=0 für e≤0.The control unit is preferably set up to regulate the support level u ₂ (t) using a PID controller. The PID controller is particularly suitable for controlling the physiological data PD(t) because its integral term helps to gradually reduce the control deviation and its derivative term allows control deviations to be corrected even before they actually occur. It is particularly preferred that the PID controller is set up to support u ₂ (t) according to $$\mathrm{and}\left(t\right)=K_P\ast {ƒ}_1\left(e\left(t\right)\right)+K_I\ast {\displaystyle \underset{\tau =0}{\overset{\tau =t}{\int }}{ƒ}_2\left(e\left(\tau \right)\right)\text{i.e}\tau +K_D\ast \frac{\text{i.e}{ƒ}_3\left(e\left(t\right)\right)}{\text{i.e}t}}$$

to be determined, where K _P , K _I and K _D are control parameters, where e(t) is the control deviation at time t, the functions f ₁ (e), f ₂ (e) and f ₃ (e) being chosen in this way that underestimation errors are weighted more heavily than overestimation errors. As a result, deviations of the controlled variable to values greater than the reference variable are less likely than deviations of the controlled variable to values lower than the reference variable. This can avoid the overexertion that can cause physical harm to the driver. It is particularly preferred that $${ƒ}_1\left(e\right)={\displaystyle \sum _{i=0}^{\mathrm{<figure-callout\; id="1"\; label="p\; c\; i"\; filenames="DE102021104523B3\_0017.png,DE102021104523B3\_0018.png"\; state="\{\{state\}\}">p</figure-callout>}}{c}_i{1}_{}\ast e^i}$$

and $${ƒ}_2\left(e\right)={\displaystyle \sum _{i=0}^{\mathrm{<figure-callout\; id="2"\; label="q\; c\; i"\; filenames="DE102021104523B3\_0018.png"\; state="\{\{state\}\}">q</figure-callout>}}{c}_i{2}_{}\ast e^i}$$

and f ₃ (e) = 0 for e < 0 and f ₃ (e) = e for e ≥ 0, where in f ₁ (e) and f ₂ (e) the polynomial can be different from e in different regions. For example, the functions f ₁ (e) and f ₂ (e) can have an angle bisector and lie above the angle bisector only in a range 0<e<E ₁ or 0<e<E ₂ . For example, especially when the physiological data is a heart rate, the following can apply: f ₁ (e)=f ₂ (e)=e for e>12 or e<0 and f ₁ (e)=f ₂ (e )=2*e-0.082*e ² for 0≤e≤12. For example, f ₃ (e) can be: f ₃ (e)=e for e>0 and f ₃ (e)=0 for e≤0.

The computing unit is preferably set up to adjust the control parameters K _P , K _I and K _D individually for each person. It is particularly preferred that the processing unit is set up to carry out a calibration method in which a step response of the physiological data PD(t) or the exertion data A(t) is generated by an abrupt change in the manipulated variable, with the processing unit being set up to Step response to determine the control parameters K _P , K _I and K _D.

It is preferred that the land vehicle is an electric bicycle. The electric bicycle can also be a pedelec. The pedelec is an electric bicycle in which the control unit is set up to control the motor power P _M (t) provided by the motor to drive the land vehicle as a function of the support level u(t) and the power P(t) of the driver.

• 1 zeigt eine schematische Ansicht zu einem erfindungsgemäßen Landfahrzeug.
• 2 zeigt einen ersten Programmablaufplan.
• 3 zeigt einen zweiten Programmablaufplan.
• 4 zeigt eine erste Auftragung verschiedener während einer Fahrt mit dem Landfahrzeug aufgenommener Messdaten.
• 5 zeigt eine zweite Auftragung verschiedener während einer Fahrt mit dem Landfahrzeug aufgenommener Messdaten.

The invention is explained in more detail below with reference to the accompanying schematic drawings.

• 1 shows a schematic view of a land vehicle according to the invention.
• 2 shows a first program flowchart.
• 3 shows a second program flow chart.
• 4 shows a first plot of various measurement data recorded during a trip with the land vehicle.
• 5 shows a second plot of various measurement data recorded during a trip with the land vehicle.

like it out 1 As can be seen, a land vehicle 5 is set up to be driven by a driver's muscular power and has an engine 9 which is set up to drive the land vehicle 5 . The land vehicle 5 has an effort measuring device 6, which is set up to measure an effort A(t) of the driver caused by the application of muscle power, a speed measuring device 7, which is set up to determine a speed v(t) of the land vehicle 5, and a Control unit 8, which is set up to control the motor 9 and to determine a plurality of different driving situations of the land vehicle 5 based on the measured exertion A(t) and the measured speed v(t), one of the driving situations being a starting situation 1 and t is the time and, if the driving situation is determined as the starting situation 1, to control a support level u(t) of the motor 9 with a value u _start (t).

In 2 and 3 program flow charts are shown which illustrate how the control unit 8 can be set up to determine the different driving situations. For example, the program flowcharts can begin at start 4. 2 shows that the effort A(t) can be a mechanical power P(t), in particular a pedaling power, of the driver and that the control unit 8 can be set up to query in a first query 11 whether v(t)<S _v and P(t)<S _P , and in case the answer is yes, determining the driving situation as the starting situation 1, where S _V is a speed threshold and S _P is a power threshold. In addition, shows 2 that the control unit 8 can be set up, in the event that the answer to the first query 11 is no, to query in a second query 12 whether v(t)<S _V +C _V and P(t)<S _P +C _P and (v(t)-v(t-τ _V ))/τ _V <S _DV , and in the case that the answer to the second inquiry 12 is yes, to determine the driving situation as the starting situation 1 , where Cv is a positive constant, C _P is a positive constant, τ _V is a deceleration, and S _DV is a negative acceleration threshold.

3 shows that the driving situations can have a stable situation 0, an uphill situation 2 and a downhill situation 3, the control unit 8 being set up when the driving situation is determined as the stable situation 0, the support level u(t) with a value u _stable ( t) to control, when the driving situation is determined as the uphill situation 2, to control the assist level u(t) with a value u _to (t), and when the driving situation is determined as the downhill situation 3, to control the assist level u(t) with a value u _from (t). In summary, that
u(t)=u _start (t), if the driving situation is the starting situation,
u(t)=u _up (t) when the driving situation is the uphill situation,
u(t)=u _ab (t) when the driving situation is the downhill situation, and
u(t)=u _stable (t) when the driving situation is the stable situation. The first query 11 and the second query 12, which are 2 shown with two different diamonds are in 3 summarized in a rhombus. It applies that if the first query 11 or the second query 12 was answered with yes, in 3 the answer is yes. If both the first query 11 and the second query 12 were answered with no, in 3 the answer no.

The control unit 8 can be set up (cf 3 ), in the case that the driving situation is not determined as the starting situation 1 and that at a time t-τ the driving situation was determined as the stable situation 0 or as the starting situation 1 to query whether D(t)>S _D1 * dD(t) and in case the answer is yes, to determine the driving situation as the uphill situation 2, where τ is a sampling time of the control unit 8, D(t) a by the driver at his effort A(t) on Drive wheel of the land vehicle 5 applied force, which is in particular a rotational force, S _D1 is a constant and dD(t) is a unit-less force gradient over time of the force D(t), which is in particular according to dD(t)=1-k _D *(D( t)-D(tT _D ))/τ _D where k _D is a constant and τ _D is a delay.

The control unit 8 can also be set up (cf 3 ), in the case that the driving situation is not determined as the starting situation 1 and that at a time t-τ the driving situation was determined as the uphill situation 2, to inquire whether D(t)>S _D1 *dD(t)-H _D and in case the answer is yes, to determine the driving situation as the uphill situation 2, where τ is a sampling time of the control unit 8, D(t) is a driver's effort A(t) on a driving wheel of the land vehicle 5 applied force, which is in particular a rotational force, S _D1 is a constant, H _D is a constant and dD(t) is a unit-less force gradient over time of the force D(t) which is in particular according to dD(t)=1-k _D *( D(t)-D(t-τ _D ))/τ _D is determined, where k _D is a constant and τ _D is a delay.

The control unit 8 can be set up (cf 3 ), in the case that the driving situation is not determined as the start situation 1 and that at a time t-τ the driving situation was determined as the stable situation 0, as the start situation 1 or as the downhill situation 3, to query whether D(t )<S _D2 *dD(t) and in case the answer is yes, to determine the driving situation as the downhill situation 3, where τ is a sampling time of the control unit 8, D(t) is a time taken by the driver at his effort A (t) force applied to a drive wheel of the land vehicle 5, which is in particular a rotational force, S _D2 is a constant and dD(t) is a unit-less force gradient over time of the force D(t), which is in particular according to dD(t)=1-k _D *(D(t)-D(t-τ _D ))/τ _D is determined, where k _D is a constant and τ _{d is} a delay. For example, the query as to whether D(t)<S _D2 *dD(t) can also be made in the event that the answer to the query as to whether D(t)>S _D1 *dD(t) is no is.

like it out 3 As can be seen, the control unit 8 can be set up to determine the driving situation as the stable situation 0 in the event that the driving situation is not determined as the starting situation 1, the uphill situation 2 or the downhill situation 3.

The support level u(t) can be positive, whereby the engine drives the land vehicle, and/or negative, whereby the engine brakes the land vehicle. An example of the motor configured to propel and decelerate the land vehicle is an electric motor configured to perform regeneration, ie convert the driver's effort A(t) into electric power. For a particularly sensitive control of the motor, it is preferred that the control unit is set up to control the support level u(t) in small increments. For example, the increments can be a maximum of 3%, in particular a maximum of 1.5% or a maximum of 1%. The maximum range of the assistance level u(t) can be from 0% to 100% or, in the case that the motor is set up to brake the land vehicle, from -100% to 100%. The control unit 8 can be set up to control the engine power P _M (t) provided by the engine 9 for driving the land vehicle 5 as a function of the support level u(t) and the power P(t) of the driver. For example, the control unit can be set up to determine the engine power according to P _M (t)=u(t)*K*P(t). The factor K indicates the maximum possible motor support. K can be, for example, from 1 to 5 and is in particular 3.

The speed threshold value S _P can be, for example, from 5 km/h to 12 km/h, with low speeds being more suitable for those drivers who are untrained and high speeds being more suitable for those drivers who are well trained.

The power threshold S _P can be, for example, from 30 watts to 120 watts. Lower powers, such as from 30 watts to 75 watts, are more suitable when the land vehicle is a light electric bicycle. High powers, such as from 50 watts to 120 watts, are more appropriate when the land vehicle is a heavy electric bicycle, such as a mountain bike or has more than two wheels. It also applies here that rather low values from the respective areas are suitable for those drivers who are untrained, and rather high values from the respective areas are suitable for those drivers who are well trained.

Cv depends on the type of land vehicle. For example, Cv can be from 1 km/h to 3 km/h, where Cv=2 km/h is suitable for most electric bicycles.

For example, Cp can be from 0 to 50 watts, with the constant _Cp being from 10 watts to 20 watts suitable for most electric bicycles.

For example, the acceleration threshold S _DV can be from -1 km/(h*s) to -3 km/(h*s), where S _DV =-2 km/(h*s) for most drivers and routes that use this Land vehicle travels, is suitable.

The delay τ _V can be from 1 s to 3 s, for example. The more noise is expected in the measurement of the velocity v(t), the longer the delay τ _V should be selected. τ _V =2 s is suitable for most cases of noise.

τ can be from 0.1 s to 2 s, in particular 1 s.

S _D1 depends on the aerodynamics of the land vehicle. For example, S _D1 can be determined by the formula 0.07*M, where M is the sum of the masses of the driver and the land vehicle in kg and S _D1 is given in N. For example, for an electric bicycle as the land vehicle, S _D1 can be from 3.5N to 14N.

k can be, for example, from 0.1 s/N to 0.5 s/N.

τ _D can be, for example, from 2 s to 5 s.

H _D depends on the terrain on which the land vehicle is traveling. The hillier the terrain, the higher H _D should be selected. For example, HD can be from 0.1N to 2N, where it has been found that _HD = _0.5N is suitable for most terrain.

S _D2 depends on the aerodynamics of the land vehicle. For example, S _D2 can be determined by S _D2 =3.65N if M≤85 kg and S _D2 =4.5N-0.01*M*N/kg if M>85 kg, where M is the sum of the masses of the driver and the land vehicle is in kg and S _D2 is expressed in N. For example, for an electric bicycle as the land vehicle, S _D2 can be from 3.65N to 2.5N.

The rotational force D(t) is directed in the tangential direction of the drive wheel and can act on the outer end in the radial direction of the drive wheel.

To determine the power P(t), the effort measuring device 6 may include a torque sensor configured to measure a torque M(t) generated by the driver during his effort A(t) and an angular velocity sensor configured to to measure the angular velocity associated with the torque. The angular velocity can be a speed, for example. The power P(t) can then be determined as the product of the torque M(t) and the angular velocity. For example, the torque D(t) can be determined according to D(t)=M(t)/R, where R is the radius of the drive wheel.

According to a first embodiment of the land vehicle 5 u _start (t), u _stable (t), u _up (t) and u _down (t) can each be constants. For example, u _1,start can be from -5% to 100%, or from 0% to 100%, or from 10% to 100%. u _1,auf can be from -5% to 100% or from 0% to 100% or from 10% to 100%. u _1,stable can be from -50% to 50% or from 0% to 50%. u _1,ab can be from -100% to 5% or from 0% to 5%. It can be the case that u _1,start ≥ u _1,auf ≥ u _1,stabil ≥ u _1,ab or that u _1,auf ≥ u _1,start ≥ u _1,stabil ≥ u _1,ab .

• - für u_start(t) eine vorbestimmte Konstante u_1,start zu wählen, wenn u_1,start>u₂(t), oder für u_start(t) u₂(t) zu wählen, wenn u₂(t) > u_1,start,
• - für u_stabil(t) u₂(t) zu wählen,
• - für u_auf(t) eine vorbestimmte Konstante u_1,auf zu wählen, wenn u_1,auf>u₂(t), oder für u_auf(t) u₂(t) zu wählen, wenn u₂(t)>u_1,auf, und
• - für u_ab (t) eine vorbestimmte Konstante u_1,ab zu wählen, wenn u_1,ab>u₂(t)-u_korr, oder für u_ab(t) u₂(t)-u_korr zu wählen, wenn U2 (t) -u_korr>u_1,ab, wobei u_korr eine positive Konstante ist.

Zusammengefasst gilt:

• Ustart (t)=max[u_1,start, u₂(t)],
• u_stabil(t)=u₂(t),
• u_auf(t)=max[u_1,start, u₂(t)] und
• u_ab(t)=max[u_1,ab, u₂(t) - u_korr].
• u_korr ist abhängig von dem Landfahrzeug und dem Motor. u_korr kann von 1 % bis 50 % betragen und insbesondere für ein Elektrofahrrad von 3 % bis 5 % betragen.

According to a second embodiment of the land vehicle, the land vehicle can have a body sensor that is set up to measure physiological data PD(t) of the driver's body, and a computing unit that is set up to make a prognosis mPD(t+T) of the physiological data create, wherein the control unit 8 is set up to provide a predetermined reference variable for the physiological data PD(t), to take the prognosis mPD(t+T) as a control variable and to increase a support level u ₂ (t) of the motor 9 as a manipulated variable choose, wherein the control unit (8) is set up,

• - choose for u _start (t) a predetermined constant u _1,start if u _1,start >u ₂ (t), or choose for u _start (t) u ₂ (t) if u ₂ (t) > u _{1, start} ,
• - choose u ₂ (t) for u _stable (t),
• - choose for u _on (t) a predetermined constant u _1,on if u _1,on >u ₂ (t), or choose for u _on (t) u ₂ (t) if u ₂ (t) >u _1,on , and
• - to choose a predetermined constant u _1,ab for u _ab (t) if u _1,ab >u ₂ (t)-u _corr , or to choose for u _ab (t) u ₂ (t)-u _corr , if U2 (t) -u _corr >u _1,ab , where u _corr is a positive constant.

In summary:

• Ustart (t)=max[u _1,start , u ₂ (t)],
• u _stable (t)=u ₂ (t),
• u _on (t)=max[u _1,start , u ₂ (t)] and
• u _ab (t)=max[u _1,ab , u ₂ (t) - u _corr ].
• u _korr depends on the land vehicle and the engine. u _korr can be from 1% to 50% and in particular for an electric bicycle from 3% to 5%.

gespeichert sein, in dem $$B_1\left(t\right)={\displaystyle \sum _{i=1}^j{a}_{1i}\ast \left({\displaystyle \sum _{d=0}^{D_i}A\left(t-{\tau }_{1i}-d\ast K_i\right)/\left(D_i+1\right)}\right)}$$

und $$B_2\left(t\right)={\displaystyle \sum _{i=1}^k{a}_{2i}\ast PD\left(t-{\tau }_{2i}\right)}$$

ist, wobei die Recheneinheit eingerichtet sein kann, mittels eines Optimierungsalgorithmus die Koeffizienten a_xi, den Summanden a₁₀, die Verzögerungen τ_xi zumindest teilweise und die Verzögerung T für jeden Fahrer individuell so anzupassen, dass mPD(t+T) die gemessenen physiologischen Daten PD(t+T) annähert und anhand des Modells die Prognose mPD(t+T) der physiologischen Daten PD(t+T) zu erstellen. In dem Term B₁(t) wird eine Mittelung von Di+1 Messpunkten vorgenommen, die einen Zeitabstand K_i haben. Beispielsweise können die Werte für D_i aus einem Bereich von 0 bis 60 ausgewählt sein. Die Werte für den Zeitabstand K_i können beispielsweise aus einem Bereich von 0,2 Sekunden bis 2 Sekunden ausgewählt sein. j kann beispielsweise aus dem Bereich von 2 bis 5 ausgewählt sein. k kann beispielsweise aus dem Bereich von 1 bis 4 ausgewählt sein. Die physiologischen Daten PD(t) können eine Herzfrequenz, eine Herzfrequenzvariabilität, ein Elektrokardiogramm, eine Sauerstoffsättigung des Bluts, einen Blutdruck, und/oder eine neurologische Aktivität, insbesondere eine Elektroenzephalografie, aufweisen.In the computing unit, a mathematical model of the form $$mPD\left(t+T\right)=a_{10}+{\displaystyle \sum _x{B}_x\left(t\right)}$$

be stored in which $$B_1\left(t\right)={\displaystyle \sum _{i=1}^j{a}_{1i}\ast \left({\displaystyle \sum _{\mathrm{i.e}=0}^{D_i}A\left(t-{\tau }_{1i}-\mathrm{i.e}\ast K_i\right)/\left(D_i+1\right)}\right)}$$

and $$B_2\left(t\right)={\displaystyle \sum _{i=1}^k{a}_{2i}\ast PD\left(t-{\tau }_{2i}\right)}$$

is, wherein the computing unit can be set up, using an optimization algorithm, the coefficients a _xi , the summand a ₁₀ , the delays τ _xi at least partially and the delay T for each driver individually so that mPD (t + T) measured physiological data PD(t+T) and to use the model to create the forecast mPD(t+T) of the physiological data PD(t+T). In the term B ₁ (t), an averaging of Di+1 measuring points is carried out, which have a time interval K _i . For example, the values for Di can be _selected from a range of 0-60. The values for the time interval K _i can be selected from a range of 0.2 seconds to 2 seconds, for example. j can be selected from the range of 2 to 5, for example. k can be selected from the range of 1 to 4, for example. The physiological data PD(t) can include a heart rate, a heart rate variability, an electrocardiogram, an oxygen saturation of the blood, a blood pressure, and/or a neurological activity, in particular an electroencephalography.

4 and 5 show plots with measurement data recorded during a trip of the land vehicle, which is a pedelec. A height H(t) of the land vehicle above sea level, the support level u(t) and the power P(t) are each plotted against time t. In 4 the measurement data were recorded with a land vehicle according to the first embodiment and 5 the measurement data were recorded with a land vehicle according to the second embodiment. In 5 Figure 1 shows yet another plot of PD(t) and mPD(t+T) versus time, where it is in 5 the physiological data PD(t) is a heart rate. In both embodiments, u _1,start =25%, u _1,auf =20% and u _1,stabil =u _1,ab =1%. It can be seen that in 4 the support level u(t) changes between 25%, 20% and 1%. In 5 on the other hand, the support level u(t) can assume different values if u ₂ (t) is selected instead of u _1,start , u _1,up , u _1,stable or u _1,down .

Reference List

0

stable situation

1

starting situation

2

uphill situation

3

downhill situation

4

begin

5

land vehicle

6

effort measuring device

7

speed measuring device

8th

control unit

9

engine

11

first query

12

second query

At)

effort of the driver

v(t)

speed

P(t)

performance

p.m

engine power

u(t)

support level

t

Time

PD(t)

physiological data

mPD(t+T)

Forecast of the physiological data

Temp(t)

temperature

N(t)

Tilt

Sv

speed threshold

SP

performance threshold

CV

constant

CP

constant

τV

delay

τD

delay

τ

Sampling time of the control unit

SDV

acceleration threshold

M(t)

torque

R

radius of the drive wheel

D(t)

torque

dD(t)

torque gradient

kD

constant

SD1

constant

SD2

constant

HD

constant

unstable

Support level in stable situation

usart

Support level at start situation

up

Support level for uphill situations

etc

Support level in downhill situations

H(t)

height

Claims (15)

Land vehicle (5) which is set up to be driven by a driver's muscular power and has an engine (9) which is set up to drive the land vehicle (5), the land vehicle (5) having an effort measuring device (6) which is set up is to measure an effort A(t) of the driver caused by the application of muscle power, a speed measuring device (7) which is set up to determine a speed v(t) of the land vehicle (5), and a control unit (8), which is set up to control the engine (9) and to determine a plurality of different driving situations of the land vehicle (5) on the basis of the measured effort A(t) and the measured speed v(t), one of the driving situations being a starting situation (1) and t is the time, and if the driving situation is determined as the starting situation (1), to control a support level u(t) of the motor (9) with a value u _start (t), characterized in that that the effort A(t) is a mechanical power P(t) of the driver and the control unit (8) is set up to query in a first query (11) whether v(t)<S _V and P(t)<S _P , and in case the answer is yes, determining the driving situation as the starting situation (1), where Sv is a speed threshold and S _P is a power threshold. Land vehicle (5) according to claim 1 , where the rider's mechanical power P(t) is a pedaling power of the rider. Land vehicle (5) according to claim 1 or 2 , wherein the control unit (8) is set up, in the event that the answer to the first query (11) is no, to query in a second query (12) whether v(t)<S _V +C _V and P( t)<S _P +C _P and (v(t)-v(t-τ _V ))/τ _V <S _DV , and in case the answer to the second query (12) is yes, the driving situation as the starting situation (1), where Cv is a positive constant, C _P is a positive constant, τ _V is a deceleration, and S _DV is a negative acceleration threshold. Land vehicle (5) which is set up to be driven by muscle power of a driver and has a motor (9) which is set up for driving the land vehicle (5), the land vehicle (5) having an effort measuring device (6) which is set up to measure an effort A(t) of the driver caused by the application of muscle power, a speed measuring device (7) set up to determine a speed v(t) of the land vehicle (5), and a control unit (8). , which is set up to control the motor (9) and to determine a plurality of different driving situations of the land vehicle (5) on the basis of the measured effort A(t) and the measured speed v(t), one of the driving situations being a starting situation (1st ) and t is the time, and if the driving situation is determined as the starting situation (1), to control a support level u(t) of the motor (9) with a value u _start (t), the driving si tations have a stable situation (0), an uphill situation (2) and a downhill situation (3), the control unit (8) being set up when the driving situation is determined as the stable situation (0), the support level u(t) with a value u _stable (t) when the driving situation is determined as the uphill situation (2), control the assist level u(t) with a value u _on (t), and when the driving situation is determined as the downhill situation (3) is intended to control the support level u(t) with a value u _ab (t), characterized in that the control unit (8) is set up in the event that the driving situation is not determined as the starting situation (1) and that at a time t-τ the driving situation was determined as the stable situation (0) or as the starting situation (1), to query whether D(t)>S _D1 *dD(t) and in the event that the answer is yes is to determine the driving situation as the uphill situation (2), where τ is a sampling time t of the control unit, D(t) is a force applied by the driver at whose effort A(t) to a driving wheel of the land vehicle (5), S _D1 is a constant, and dD(t) is a unit-less force gradient over time of the force D(t). . Land vehicle (5) according to claim 4 , where u _start (t), u _stable (t), u _up (t) and u _down (t) are constants. Land vehicle (5) which is set up to be driven by a driver's muscular power and has an engine (9) which is set up to drive the land vehicle (5), the land vehicle (5) having an effort measuring device (6) which is set up is to measure an effort A(t) of the driver caused by the application of muscle power, a speed measuring device (7) which is set up to determine a speed v(t) of the land vehicle (5), and a control unit (8), which is set up to control the engine (9) and to determine a plurality of different driving situations of the land vehicle (5) on the basis of the measured effort A(t) and the measured speed v(t), one of the driving situations being a starting situation (1) and t is the time, and when the driving situation is determined as the starting situation (1), to control a support level u(t) of the motor (9) with a value u _start (t), the driving situations n have a stable situation (0), an uphill situation (2) and a downhill situation (3), the control unit (8) being set up when the driving situation is considered to be the stable situation (0) is determined to control the assist level u(t) with a value u _stable (t), when the driving situation is determined as the uphill situation (2), to control the assist level u(t) with a value u _to (t), and , if the driving situation is determined as the downhill situation (3), to control the assistance level u(t) with a value u _from (t), characterized in that the control unit (8) is set up in the event that the driving situation is not is determined as the starting situation (1) and that at a time t-τ the driving situation was determined as the uphill situation (2), querying whether D(t)>S _D1 *dD(t)-H _D and if so that the answer is yes, to determine the driving situation as the uphill situation (2), where τ is a sampling time of the control unit, D(t) is a force applied by the driver at his effort A(t) to a drive wheel of the land vehicle (5). , S _D1 a constant, H _D a constant and dD(t) a unitless force gradient over time d he force D(t) are. Land vehicle (5) which is set up to be driven by a driver's muscular power and has an engine (9) which is set up to drive the land vehicle (5), the land vehicle (5) having an effort measuring device (6) which is set up is to measure an effort A(t) of the driver caused by the application of muscle power, a speed measuring device (7) which is set up to determine a speed v(t) of the land vehicle (5), and a control unit (8), which is set up to control the engine (9) and to determine a plurality of different driving situations of the land vehicle (5) on the basis of the measured effort A(t) and the measured speed v(t), one of the driving situations being a starting situation (1) and t is the time, and when the driving situation is determined as the starting situation (1), to control a support level u(t) of the motor (9) with a value u _start (t), the driving situations n have a stable situation (0), an uphill situation (2) and a downhill situation (3), the control unit (8) being set up when the driving situation is determined to be the stable situation (0), the support level u(t) having a value u _stable (t) when the driving situation is determined as the uphill situation (2), control the assist level u(t) with a value u _on (t), and when the driving situation is determined as the downhill situation (3) is intended to control the support level u(t) with a value u _ab (t), characterized in that the control unit (8) is set up in the event that the driving situation is not determined as the starting situation (1) and that at a time t-τ the driving situation was determined as the stable situation (0), as the starting situation (1) or as the downhill situation (3), to query whether D(t)<S _D2 *dD(t) and in in the case that the answer is yes, to determine the driving situation as the downhill situation (3), where at τ a sampling time of the control unit, D(t) a force applied by the driver during his exertion A(t) on a drive wheel of the land vehicle (5), S _D2 a constant and dD(t) a unit-less force gradient over time of the force D( t) are. Land vehicle (5) according to any one of Claims 4 until 7 , where D(t) is a torque and/or where dD(t) is determined according to dD(t)=1-k _D *(D(t)-D(t-τ _D ))/τ _D , where k _D is a constant and τ _D is a delay. Land vehicle (5) according to any one of Claims 4 until 8th , wherein the control unit (8) is set up, in the case that the driving situation is not determined as the starting situation (1), as the uphill situation (2) or as the downhill situation (3), the driving situation as the stable situation (0) to determine. Land vehicle (5) according to any one of Claims 1 until 9 , the control unit (8) being set up to increase the engine power P _M (t) provided by the engine (9) for driving the land vehicle (5) as a function of the support level u(t) and the power P(t) of the driver Taxes. Land vehicle (5) according to any one of Claims 1 until 3 , wherein the land vehicle has a body sensor that is set up to measure physiological data PD(t) of the driver's body, and a computing unit that is set up to create a forecast mPD(t+T) of the physiological data, the control unit (8) is set up to provide a predetermined command variable for the physiological data PD(t), to take the prognosis mPD(t+T) as a controlled variable and to select a support level u ₂ (t) of the motor (9) as a manipulated variable , wherein the control unit (8) is set up to select a predetermined constant u _1,start for u _start (t) if u _1,start >u ₂ (t), or for u _start (t) u ₂ (t) to be chosen if u ₂ (t)>u _1,start . Land vehicle (5) according to any one of Claims 4 and 6 until 10 , wherein the land vehicle has a body sensor that is set up to measure physiological data PD(t) of the driver's body, and a computing unit that is set up to create a forecast mPD(t+T) of the physiological data, the control unit (8) is set up to provide a predetermined reference variable for the physiological data PD(t), to take the prognosis mPD(t+T) as a controlled variable and to select a support level u ₂ (t) of the motor (9) as a manipulated variable , wherein the control unit (8) is set up - to select a predetermined constant u _1,start for u _start (t) if u _1,start >u ₂ (t), or for u _start (t) u ₂ (t ) to choose if u ₂ (t) > u _1,start , - choose for u _stable (t) u ₂ (t), - choose a predetermined constant u _1,auf for u _on (t) when u _{1, up} >u ₂ (t), or for u _up (t) u ₂ (t) if u ₂ (t)>u _1,up , and for u _down (t) a predetermined constant u _1,down to be selected if u _1,ab >u ₂ (t)-u _corr , or to be selected for u _ab (t) u ₂ (t)-u _corr if U2 (t) -u _corr >u _1,ab , where u _korr is a positive constant. Land vehicle (5) according to claim 11 or 12 , where in the arithmetic unit is a mathematical model of the form $$mPD\left(t+T\right)=a_{10}+{\displaystyle \sum _x{B}_x\left(t\right)}$$

is stored in which $$B_1\left(t\right)={\displaystyle \sum _{i=1}^j{a}_{1i}\ast \left({\displaystyle \sum _{\mathrm{i.e}=0}^{D_i}A\left(t-{\tau }_{1i}-\mathrm{i.e}\ast K_i\right)/\left(D_i+1\right)}\right)}$$

and $$B_2\left(t\right)={\displaystyle \sum _{i=1}^k{a}_{2i}\ast PD\left(t-{\tau }_{2i}\right)}$$

is set up, by means of an optimization algorithm, the coefficients a _xi , the summand a ₁₀ , the delays τ _xi , at least in part, and the delay T for each driver are individually adjusted in such a way that mPD(t+T) corresponds to the measured physiological data PD (t+T) and to use the model to create the prognosis mPD(t+T) of the physiological data PD(t+T). Land vehicle (5) according to claim 12 or 13 , the physiological data PD(t) having a heart rate, a heart rate variability, an electrocardiogram, an oxygen saturation of the blood, a blood pressure, and/or a neurological activity, in particular an electroencephalography. Land vehicle (5) according to any one of Claims 1 until 14 , wherein the land vehicle (5) is an electric bicycle.

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