JP2020062906A - Estimated power generation and charging control method for range extender vehicle - Google Patents

Abstract

To provide an estimated power generation and charging control method for a range extender vehicle, which makes a driving plan before driving by obtaining information on driving routes with ICT technologies such as GIS or GNSS and utilizing a variety of consolidated data required for driving on temperatures outside the vehicle or outside conditions in silent sections in the middle of driving, and appropriately incorporates driving section and time of the generator into the driving plan.SOLUTION: In an estimated power generation and charging control method proposed by the present invention, a driving plan is made before driving, and thus driving and stopping of a generator is appropriately controlled during driving. Consequently, the generator and a secondary cell can be reduced in size, and exhaust gas can be reduced; therefore, low carbonization can be promoted.SELECTED DRAWING: Figure 7

Description

  The present invention relates to a predictive power generation charging control system mounted on a range extended-electric vehicle (EV) vehicle in which a secondary battery is charged by an engine generator and a motor is driven by the secondary battery to run.

EV vehicles driven by secondary batteries are attracting attention as a clean transportation system that emits no carbon dioxide (CO2). The first reason is that, unlike a vehicle that runs on an internal combustion engine, it runs on a motor driven by the electric power stored in a secondary battery, so it emits no CO2, is quiet, and has excellent riding comfort. The second reason is that maintenance costs including fuel costs are cheaper than vehicles such as diesel engines, so it is considered to have a great advantage.

  However, the price of an EV bus, which is a type of current EV vehicle, depends on the modification of a bus equipped with a diesel engine, so it is necessary to mount a large amount of expensive secondary batteries, so The initial investment is several times more expensive than the bus, and its introduction has not progressed easily. Further, in EV trucks, their widespread use has been delayed due to reasons such as inconvenience in that a large amount of secondary battery space reduces the loading capacity of the truck.

  In addition, the current secondary battery technology is not easy to use, because the driving distance is insufficient and the charging time is long. Although the adoption of ultra-quick charging technology that has improved the problem of charging time has been demonstrated, it is difficult to install charging equipment on the route, so it must be placed in a place where bus operators and truck operators can perform maintenance. However, there is a problem that the operation until stopping there for charging is wasted. In addition, the driver's wage accounts for a large proportion of the cost of bus and truck operators, so that the charging time and the time for heading to the charging are wasted time and increase in cost. On the other hand, next-generation rechargeable batteries with large charging capacity and short charging time are being developed, but there is nothing that can be called a decisive hit at this point, and we hope to accelerate technological development.

As prior art documents, "electric bus and charging system (JP-A-2016-181965)" and the like have been proposed. However, in this proposal, the charging timing of the secondary battery is performed by using the time for the passenger to move up and down. However, since the time for raising and lowering is generally short, sufficient charging may not be possible.

It has already been mentioned that EV requires a large capacity battery in order to secure the mileage, and the charging time becomes long, but as a solution to this, the series hybrid system has been applied to passenger cars. In general, this technology uses an existing engine as a generator, mounts a small capacity secondary battery, almost always drives the engine to charge the secondary battery, and uses the power of the secondary battery to drive the motor. It is driven to move the vehicle. However, when it is applied to a commercial vehicle such as a bus or a truck, it is necessary to supply an excessive amount of instantaneous electric power required for a steep uphill or the like, and thus a large generator and a large amount of secondary batteries are required. As a result, space is taken up, the number of seats is reduced in buses, and the cargo loading capacity is limited in trucks, so it is extremely difficult to make a commercial vehicle series hybrid.

On the other hand, the range extender EV (RE_EV) vehicle of this technology utilizes geographical information system (GIS) and GNSS (Global Navigation Satellite System) to obtain position information and altitude difference on the driving route. Is collecting road surface information. Furthermore, by using the driving data accumulated during the driving so far, a power generation plan (driving plan) is formulated before driving. In this way, by planning a travel plan for the day before traveling, the required amount of power generation can be calculated in advance, so that appropriate power generation and charging can be performed, and therefore the generator and the secondary battery can be downsized. After the start of the traveling, the traveling can be performed according to the plan by traveling while correcting the traveling plan based on the traveling data that is sequentially obtained during traveling. In addition, it is possible to further improve fuel efficiency if external charging can be performed during traveling.

As described above, in the range extender vehicle, the engine is driven to charge the secondary battery only when the amount of charge in the secondary battery becomes small. Normally, the motor is driven only by the secondary battery without driving the engine, so there is no concern about running out of electricity during running like EV vehicles, and the limitation of mileage, which was a problem for EV vehicles, should be eliminated. This makes it possible for the vehicle to be extremely convenient. In addition, since this Range Extender EV vehicle runs on a motor with a secondary battery for most of its running time, it is a clean transportation system that emits significantly less carbon dioxide than ordinary engine-powered vehicles. The engine sound from the car is limited, resulting in a quiet and comfortable ride for a considerable amount of travel time. And maintenance costs including fuel costs are cheaper than diesel engine vehicles, so it has been considered to be a great advantage.

  The proposer has previously made a patent proposal in which such a range extender technology is applied to a bus, which is one of the main vehicles of a public transportation system (Japanese Patent Application No. 2017-204209). The proposal is that even for trucks that do not travel on a planned circular route, such as buses, it is possible to formulate a power generation plan before traveling by using position information on the traveling route and road surface information such as altitude difference. The range extender technology can be applied to commercial vehicles.

  As a prior art similar to this proposal, there is an "electric vehicle navigation system (Japanese Patent Laid-Open No. 8-240435)" that controls driving of a generator mounted on a vehicle by detecting map information, GPS information, and remaining battery capacity. This proposal suggests that hybrid vehicles, up to that point, are close to pollution-free areas in response to the problem that exhaust gas is emitted even in pollution-free areas by driving the generator installed in the vehicles when the battery capacity becomes low. In addition, when the battery level is low, the generator is driven to charge the battery, and in a pollution-free area, the generator is stopped to prevent emission of exhaust gas. Therefore, it is claimed that the exhaust gas can be prevented as much as possible in the pollution-free area. By making full use of modeling and control methods to suppress power consumption, it is possible to downsize the generator and use a small-capacity secondary battery, which does not affect the loading capacity, so so-called series hybrid technology is also used in commercial vehicles. It makes it possible.

The engine is assumed to be a small diesel engine in the following description, but the engine is not limited to this, and may be a gasoline engine, a fuel generator (so-called fuel cell), or the like.

JP, 2016-181965, A JP-A-8-240435

The problem to be solved by the present invention is that the series hybrid vehicles so far have a large number of secondary batteries and a large-sized generator to be installed in the bus in order to prepare for traveling on a steep slope, and the number of seats on the bus may be large. Then, there was a problem that the cargo loading capacity was sacrificed. Furthermore, the engine for large generators had a problem in fuel consumption and CO2 reduction proportional to it.

In this proposal, by utilizing ICT such as GIS and GNSS before traveling, a power generation plan is prepared before traveling by obtaining various information on the traveling route, so that the rechargeable battery can be selected at an optimal timing. This article describes the predictive power generation and charging control technology used in range extender vehicles that can be equipped with smaller engine generators and smaller capacity secondary batteries as a result of starting and stopping charging.
In the prior art, Japanese Patent Laid-Open No. 8-240435, the focus is on stopping the engine only in that section in order to reduce exhaust gas in the pollution-free area while driving, so the driving route is as proposed. It does not take into consideration the overall driving conditions (for example, slopes, traffic jam information, silent sections, etc.).

  Further, in the previous proposal (Japanese Patent Laid-Open No. 2016-181965), by utilizing the fact that the traveling route is determined in the case of the regular service bus, the drive and stop control of the generator are controlled according to the traveling state and the traveling environment. It was controlled so that it would be optimal. However, even if the destination changes every day like a delivery truck, by extracting the driving route information to the destination and various driving conditions before driving, the same plan as the regular service bus Driving is possible. As a result, it is possible to reduce fuel consumption (reduce CO2 emissions) and to drive in consideration of the local living environment, making it easy for bus operators and truck distributors to introduce range extender vehicles.

In recent years, map information such as GIS can use elevation data in addition to horizontal position data. These are easily available via the Internet, and the Geographical Survey Institute of Japan provides elevation data every 5 m, and the private sector uses this data after processing it for ease of use. It is expected that such services will expand overseas in the future. In this proposal, the energy model shown below is created using these data, and the system is downsized by controlling the generator. As a result, the range extender technology is applied to commercial vehicles.

The travel route is regarded as a set of minute sections n, and these minute sections are set as unit sections. Dividing the electric power required for unit travel into the electric power Ph (n) required for horizontal movement and the electric power Pv (n) required for vertical movement, the total electric power Pn required for traveling is as follows. .
_Destination
Pn = Σ (Ph (n) + Pv (n)) = ΣPh (n) + Σm (i) * g * h (i) −Σk (j) * m (j) * g * h (j)
^{Departure ground slope section i Downhill section j}
Here, m (i) and m (j) are vehicle weights in the section, and h (i) and h (j) are vertical distances in the section. Further, if the average electricity cost in the unit section of horizontal movement is C (n) and the distance is L (n), the electric power for each unit section required for horizontal movement is as follows.

Ph (n) = C (n) * L (n)

Also, the electric power required to move in the vertical direction can be obtained by the following.

Pv (n) = K (n) * m (n) * g * h (n)

Here, K is K (n) = + 1 if the section is an uphill, and K is a regeneration coefficient on a downhill, and k (n) is negative. Also, g is the acceleration of gravity of 9.8 m ² / s ² . From the above, the total electric power Pn required for traveling can be obtained.

On the other hand, the electric power Ps to cover the consumption of the traveling motor and auxiliary equipment of the vehicle while traveling is the sum of the electric energy Pi from the external charging before traveling and the total electric energy ΣPg (n) of the power generation section during traveling. Become.

Ps = Pi + ΣPg (n)

Here, the generated power Pg (n) in the unit section n is expressed as follows if the average speed of the section is SPD (n), the generator output is G (kW / h), and the section distance is L (n). To be done.

Pg (n) = G * L (n) / SPD (n)

From these, the electric power Ps that can be used during traveling can be obtained. From the above, the travelable condition is Ps> Pn, and it is only necessary to create a power generation plan that considers the amount of power Pi in external charging so that this condition holds.

A power generation plan is created as follows at what timing the total sum ΣPg (n) of generated power is generated. Utilizing GIS, the altitude difference data of the unit section is acquired, and the distance L (n) for each unit section, section average electricity cost C (n) for horizontal movement, vehicle speed SPD (n), vehicle weight m (n), The altitude difference h (n) and the regeneration coefficient k (n) are used to make the following. The total amount of generated electric power ΣPg (n) required during traveling is calculated from the equations shown so far as follows.

ΣPg (n) ＝ Ps−Pi

This total power generation amount ΣPg (n) is appropriately distributed in the travel route by considering the silent section and the regenerative power recovery section, and the amount of power generation in which section (power generation x power generation section). To do.

As an appropriate distribution method, power generation is started when the SOC (State of Charge) of the secondary battery reaches the lower limit value, and stopped when the upper limit value is reached. Basically, the lower limit value is the minimum value required for charging the secondary battery (10% as an example), and the upper limit value is the maximum value in a fully charged state (90% as an example). When the electric energy corresponding to the SOC value of the secondary battery is Sc, it is expressed by the following formula.
_{Current value Current value Current value Current value Current value}
Sc = Pi + ΣPg (n)-(ΣPh (n) + Σm (i) * g * h (i) -Σk (j) * m (j) * g * h (j))
^{Departure point Departure Ground uphill section i Downhill section j}
In the basic driving plan, Sc is set to reciprocate between the minimum value and the maximum value of the secondary battery, but if a steep long slope exists at the destination, a large amount of electric power is required, so the lower limit value is set. Drive the generator before charging. Also, if there is a steep long downhill ahead and a large amount of regenerative power can be expected, control is performed so that the regenerative power can be collected without waste by stopping the generator before reaching the chargeable upper limit of the charger. .

Fig. 1 shows an example of changes in SOC indicating the state of charge of the secondary battery created by the travel plan with respect to the travel distance. The vertical axis represents SOC and the horizontal axis represents mileage. It shows a case where the secondary battery is fully charged before traveling and then traveling is started. In section A when the vehicle starts running, EV traveling is performed with the generator stopped. Although it is possible to drive to the lower limit as it is, it is known that there is a region in front of the drive where the generator cannot be driven (for example, a quiet area such as a hospital area), so drive the generator in section B. Charge the secondary battery. Since C is a quiet area, the generator has stopped. D is charged because it exceeds the silent section, but there is a long steep downhill in section F, and a large amount of regenerative power is expected to be collected, so the generator is stopped before reaching the upper limit. E is the EV traveling section, and F is the long downhill and shows the charging state of the secondary battery by the regenerative power. Since it was possible to charge to the upper limit value with regenerative power, EV is running in G, but there is a steep uphill (I area) ahead, so power is generated in section H. Since I is a steep climb, the rate of decrease in SOC is large. At the destination, the SOC (State of Charge) is planned to be at the lower limit, so power will be generated again in Section J, and then the EV will be reached while reaching the end point.

As described above, the start and stop timings and sections of the generator are created as a travel plan before traveling, and the vehicle starts traveling along this. Then, because a deviation from the travel plan (error) occurs during the actual travel, travel is performed while sequentially correcting it using information from GIS and GNSS. In the case of actual commercial operation, the location information of the departure point and the destination point based on the delivery plan, the route setting using the navigation, the estimated arrival time, and the speed of each section during route operation are taken into consideration. A travel plan is created.

Fig. 2 shows the time when the vehicle travels along the planned route according to the travel plan, obtaining position data and elevation data from GIS and GNSS for each unit section, and at the same time, passing the unit section distance L (n) and speed SPD (n). It shows an image of calculating the horizontal and vertical movement energies required for each unit distance by calculating Tps (n). The left figure is an image of the calculation of the horizontal movement energy of the vehicle. Rotational energy proportional to the radius r is generated in the curve. In addition, the right figure is an image of calculating the vertical movement energy.
This movement energy is calculated even while driving in order to verify whether there is a large deviation in the original plan due to the unexpected unexpected traffic congestion.

  FIG. 3 shows a control method of this system as a transition diagram. Start from the starting point and enter the generator stop circle on the left. If there is an item that is satisfied in the power generation start condition, move to the right and drive the generator. After that, if the power generation stop condition is met, the generator is stopped and moved to the left area. In this way, the generator is stopped and driven repeatedly, and when it reaches the end point of the destination, it exits from the generator stop circle.

   FIG. 4 shows a simplified flowchart of the control of this system. Before travelling, information on the travel route from the current position to the destination is acquired from GIS and GNSS, and a travel plan is created in consideration of the travel data (vehicle speed, electricity cost, etc.) of the vehicle obtained from the past travel records. To do. After that, control is started according to the flowchart. First, it is determined whether the generator is in a start state or a stop state (usually a stop state at the start of traveling).

If stopped, follow the flow on the left. Numerical value (Sc) that indicates the SOC power amount of the charger and the lower limit value (ScL) of the SOC power amount + energy required to climb a hill in that section (α) + energy required to pass through a silent area When (c) is compared, if Sc is greater, the generator runs with the generator stopped, and it is determined whether or not the end point has been reached. However, if it has not reached the end point, the process returns to the beginning of the flow, and the deviation from the travel plan is corrected using the vehicle speed, electricity cost, SOC information, battery level, etc. obtained during the travel up to that time to update the travel plan. Again, Sc is compared with the required energy, and if it is determined that the remaining battery level is insufficient, the flow moves to the right side of the flow and charging by the generator is started.

On the other hand, in the judgment at the beginning of the flow, if the generator is activated, the flow moves to the right. Here, if the remaining power amount (Sc) of the battery is larger than the upper limit value (ScH) of the SOC power amount-the regenerative energy of the section, the generator is stopped and the flow proceeds to the left side. However, when Sc is low, the generator is driven as it is, but when the silent section is reached, the generator is stopped and the flow moves to the left side. If it is not in the silent section, follow the flow. If Sc is greater than the battery level set at the end point (destination), follow the flow as it is, and drive the generator to the point where Sc converges to the set value at the end point. After the point, stop the generator and head towards the end point.

 However, if it is found that the set value is not reached at the end point even if the generator is driven, the output of the generator is increased and the flow returns to the upper side. As long as the vehicle travels according to the initially planned power generation, Sc is set to converge to the set value at the end point of the destination, but for example, the auxiliary battery (air conditioner, etc.) was used more than planned during traveling, and the remaining battery level reached When it is lower than expected, SOC may be lower than expected.

5a and 5b show the situation of (2) in FIG. With respect to the lower limit value ScL of Sc and the set value ScT1, it is possible to approach the respective set values by stopping the generator at XL or XT1 while the vehicle is running. However, when the set value is ScT2, it is not possible to approach that value even with the generator running, so the output of the generator is increased as in (2). Figure 5b shows where to stop the generator. Further, (3) in the figure shows a situation where the vehicle can travel to the destination by initial charging before traveling.

FIG. 6 shows the input information, the processing algorithm, and the output information of the predictive power generation charging control using IT. As the initial information, the vehicle class information is input by inputting the information such as the size and type of the vehicle only when the predicted power generation and charging control system device is first installed in the vehicle. After that, if the travel destination and route for the day have been determined, enter the travel route.If the travel route has not been determined, this system presents the optimum route and other candidate routes, and the administrator or driver Can be selected by the person. Alternatively, the system can automatically determine the optimum route.

  While driving, the current position, SOC, vehicle speed, air conditioner and other operating conditions are automatically entered. Vehicle weight also affects fuel efficiency. Although it is considered that the weight of the car body itself is constant, the total weight of trucks changes due to loading and unloading of cargo, and the total weight of buses changes depending on passengers getting on and off. For this reason, it becomes necessary to determine the change in the total weight during traveling. For example, in a truck, the power consumption of the drive motor is monitored, and since the potential energy change can be obtained from the difference between the power consumed in a certain section of the level ground and the power consumption in a certain section where there is a difference in height, the potential energy equation (mxgxh) Weight m can be obtained. Alternatively, if the load of the cargo and the weight of the vehicle without passengers are known, the total weight can be calculated from the degree of deterioration in fuel consumption when carrying the cargo or passengers. Further, in the case of a bus, the number of passengers can be known from the loading and unloading of passengers. Therefore, assuming an average weight, a weight change within an allowable error can be obtained.

  Next, the processing algorithm section formulates a plan for power generation and charging by grasping the route and calculating the amount of electric power required to reach the destination. Furthermore, the output information includes start / stop instruction information for the generator, and the driving information for each vehicle for the driver and vehicle headquarters (control center, etc.), such as running position, speed, SOC, engine operating status, and purpose. Information such as driving situation prediction information to the ground, vehicle interior temperature, and changes in total vehicle weight are provided.

Figure 7 shows a vehicle equipped with a predictive power generation charging control system, and a vehicle headquarters (a bus center for buses, a control facility for trucks, etc.) that is a ground-side system that monitors each vehicle and gives instructions for coping with problems. ) Is a main schematic view of FIG. It also shows a charging system (CHAdeMO quick charger, etc.) installed at an appropriate location along the driving route.

 In the figure, reference numeral 100 denotes the entire configuration of a range extender (RE-EV) vehicle, 101 is a block of only an electric drive unit, and mainly an EV motor inverter block 102 for driving the vehicle, an EV drive battery 103, and an EV. The control device 104 and the like are included. Further, 105 is a communication device that communicates with the ground system, and 106 is a GNSS (Global Navigation Satellite System) position information device. Numeral 107 is a predictive power generation and charging control device itself, and has a role of outputting position information and the like from GIS and GNSS and outputting power generation start and stop instructions to the power generation unit 108. In addition, 109 is a charging system (CHAdeMO quick charger, etc.) installed on the driving route, and if the battery can be charged from outside when a long time such as a break can be taken, the operating time of the generator can be increased. As a result, fuel consumption can be reduced and CO2 emissions can be suppressed accordingly.

  FIG. 8 shows an algorithm (200) of the predictive power generation charge control technique. This system uses the GNSS position information 201 and the map information from the GIS 202 to acquire the current position of the vehicle on the travel route. Further, from the vehicle body 203, information such as SOC of the vehicle running state 204, vehicle speed, electric power required for air conditioning, outside air temperature, change in vehicle weight, etc. is acquired. At 205, the amount of electric power required for horizontal movement to the destination is calculated from the information at 202 and 203. Further, at 206, the amount of electric power converted from the potential energy for lifting the vehicle in the vertical direction on a slope or the like and the recovered power recovered on the slope down are calculated, and at 207, the remaining amount of the secondary battery is calculated. At 208, the amount of electric power required to reach the destination is extracted in real time from these three pieces of information 205, 206, and 207 (specifically, the planned amount of power generation and the timing of power generation start and stop are calculated). Upon receiving the information, the RE power generation unit control signal generator 209 instructs the RE power generation unit 210 to generate power and stop. Reference numeral 211 denotes an in-vehicle computer that implements these algorithms.

  Next, the outline of the operation of the predictive power generation charging control technique will be described with reference to FIGS. 9a, 9b, and 9c. The numbers on the left side of each figure are the numbers on the right side. Reference numeral 10 shows a cross-sectional view of the travel route (route A), in which the vertical axis represents elevation and the horizontal axis represents distance. 11 is a flat road, 12 is an uphill road, 13 is a short flat road, 14 is a downhill road, and 15 is a flat road to the end point. Here, it is assumed that the vehicle maintains a constant speed on any road. 20, the vertical axis represents power consumption (kW), and the horizontal axis can be converted into time assuming that the vehicle speed is constant anywhere on the road. Note that 12 and 14 are sloped roads, so the distance is longer than on flat roads. Here, assuming that the power consumption of the flat roads 11, 13, 15 is a, the power consumption of the uphill road 12 is b, and the regenerative power of the downhill road 14 is c, the square areas below the wavy line are the respective roadways. Power consumption (kWh). The area of 21, 22, 23, 25 represented by each triangle of the same area is also the power consumption. Since the downhill regenerates power, the amount of power generated is 24.

  Reference numeral 30 shows the transition of the remaining amount of power (SOC) of the battery. Initially the SOC was A, but as the vehicle traveled, it consumed power and gradually decreased. The triangle (21) that can be drawn from A to B is similar to the power consumption 21 of the same road in Fig. 20 above, so it is represented by the same area for simplification. Similarly, when each power consumption shown by the triangles of the other running paths in the above FIG. 20 is transferred to the SOC graph, 22 becomes (22), 23 becomes (23), and 25 becomes (25). Becomes (24), so that a graph of SOC change can be drawn as a result. In the example of 30, the SOC becomes F at the end point and becomes the lower limit value of SOC, and the vehicle can travel with only the initial charge amount, which is an example of the most efficient driving.

  Reference numeral 40 in FIG. 9b is an example of A'where the charge amount before traveling is smaller than that in the case of FIG. 30 above. The change in SOC is similar to the case of 30, but since SOC falls below the SOC lower limit between B'and C'during running, it is expected that there will be an electrical shortage and driving will not be possible. Therefore, to make F'become F '', B'can be made B '' (B ''-B '= F' '-F'), and the insufficient amount of power is the SOC lower limit. Since it is the sum of the areas of the following triangles, the amount of deficit P4 is P1 + P2 + P3-Pg in the expression obtained by subtracting Pg from the value obtained by adding P1, P2 and P3. Note that Pg is the regenerative electric energy. By generating the electric power P4 equal to the insufficient electric power in advance, it becomes possible to drive without causing a power failure.

  50 shows the case where the power generation output of the generator is d, and power generation is started from T1 so that P5 = P4. The generator output of 60 is stronger than that of the case where the output e of the generator is 50.

  70 indicates a case where there is a hospital or the like in the middle of the runway 11 and the section is a silent section and the generator needs to be stopped, so power is generated separately in P7 and P8 (P7 + P8 = P6). If the generator output of 80 is strong and the increase ratio R2 of P9 is larger than the decrease ratio R1 of SOC of P1, the power generation can be started before T5 when SOC does not fall below the SOC lower limit. The degree of freedom of In this example, in the case of P9, the power generation start is T5 immediately before it falls below the SOC lower limit, but it shows that power generation can be started even before T5 as in P10 or P11.

  Further, 90 in FIG. 9C shows an example in the case where the traveling route is changed (routeB) during traveling of 10. If the driving route changes at point X and the driving route changes to 11 ', 12', 13 ', it is necessary to immediately re-estimate the change in SOC on the new driving route. The flat road is changed from 10 to 11 ', but as shown by 100, the power consumption a does not change, so the power consumption of 21 is changed to the area of a triangle of 31. 12 'is a steep climb, so the power consumption increases significantly to c. Therefore, the power consumption is 32 triangular areas. After passing the uphill, the power consumption is 33 because it is a flat road to the end point.

  On the other hand, as shown at 110, the SOC change was (21) before the change of the traveling route, but it is switched to (31) because of the change of the route. After that, the SOC suddenly drops due to a steep climb, and falls below the SOC lower limit on the way from I to J. In order to avoid this situation, it is necessary to modify the power generation plan immediately at X when the vehicle recognizes the change of the traveling route. The insufficient power consumption is P12 + P13, which is the sum of the power consumption below the SOC lower limit, and the total P14 can be calculated.

  120 is the case where the generator output is f, and even if power generation is started at T6, which is later than X in time, the generated power amount P15 can be made equal to the insufficient power amount P14, and thus the vehicle can travel. However, in the case of 130, since the generator output g is low, it was necessary to start power generation at T7, which has already passed in time, in order to obtain the generated power amount P16 equal to the insufficient power amount P14. Therefore, it can be seen that it is necessary to increase the output of the generator, stop by the charging station to charge the battery, or select another travel route in order to avoid a power shortage after this.

In this way, the predictive power generation charging control is a technology that allows one to make a travel plan (power generation plan) in advance by utilizing GNSS and GIS that the information on the travel route before departure is one of the ICT technologies. . Furthermore, it is a technology that enables efficient driving by constantly updating the power generation plan based on the latest information from GNSS and GIS even while driving. Next, the operation of the predictive power generation control technology will be described in more detail.

  FIG. 10 shows more specifically the state of the predictive power generation charging control during traveling. In this example, the speed of the vehicle is changed on a flat road and a slope. In addition, since the slope on the actual road is considered to be much smaller than the horizontal distance on the flat road, it is considered that the slope on the actual road is very small. Here, the upper figure shows a topographic map, and the lower figure is a power map. The horizontal axis in the above figure shows distance, but the horizontal axis in the following figure can be converted to the time axis by considering the speed during running. Each line in the figure below represents the following. A shows how the SOC value before running increases due to power generation during running, B shows the transition of SOC during running, C shows the increase in power consumption due to running, and at the end point it is consumed during running. The total power consumption is shown.

  Here, the value obtained by subtracting C from A is expressed as the change in SOC of B. The power consumption of C during traveling is considered to be 1 per unit time on the flat road 11 and 2 per unit time on the uphill 12. Further, in this example, regenerative electric power is not incorporated because the downhill 14 also consumes 1 per unit time. When SOC decreases due to power consumption due to running and reaches a predetermined value (4 kW in this example), the generator is driven to start charging the secondary battery. If the power generation amount at this time is 3 power generation per unit time, it is more than 2 consumption per unit time on the uphill 12, so the SOC is increasing, and the timing to stop power generation is when the SOC reaches the upper limit value. is there. However, when it is determined that the amount of power generation is small and the SOC on the uphill cannot be recovered, the power generation start time of the generator is further advanced and the amount of power of the secondary battery is increased.

  In this way, the travel route is divided into small sections, and the travel route information at the division points is obtained from GIS and GNSS, so that a travel plan (power generation plan) can be made in advance, and elevation information can be obtained in real time during travel. It is possible to optimally control power generation and charging by obtaining the GIS and the vehicle position information from the GNSS.

Fig. 11a is a cross-sectional view of the travel route used to perform SOC simulations for the route from Tokyo to the Numazu, over Hakone Pass, with and without predictive power generation charging control. The horizontal axis shows the traveling distance and the vertical axis shows the altitude. Further, in FIG. 11b, the horizontal axis indicates the location (a, b, etc.) of each traveling point on FIG. 11a, and the vertical axis indicates the SOC. After starting from Tokyo, I traveled on an EV in a flat area for a while, but when I entered Hakone and approached Hakone Pass, the altitude increased at a stretch, so the amount of battery charge decreased significantly. The state is the part from e to f in FIG. 11b, and the SOC is rapidly decreasing. However, when the predictive power generation charge control is used, the amount of electric power required to cross the pass can be calculated when the power generation plan before traveling is calculated, so that SOC of a before reaching the lower limit (10% in this example) can be calculated. By starting power generation at the point, you can charge the battery with sufficient power and run on Hakone Pass without problems. However, if the predictive power generation charge control is not used, the power generation will start when the SOC reaches the lower limit, so sufficient power cannot be stored in the battery, and the vehicle will be running uphill on the Hakone Pass (e You can see that there is a shortage of electricity between (between f and f).

Of course, if you have a battery that can charge a sufficient amount of battery and a powerful generator, you can run without using predictive power generation charge control technology, but in that case there are many problems as described above. Can happen. First, a large number of batteries and a large generator occupy a large amount of space and weight, which affects the indoor space on the bus and reduces the installed capacity on the truck. Furthermore, due to the increased weight, there is a concern that fuel efficiency will deteriorate, and it will spoil the advantages of low fuel consumption, which was an advantage of Range Extender EV vehicles, and the low CO2 emissions that accompany it. .

The present invention provides an EV vehicle that drives a motor driven by a battery, a so-called range extender EV vehicle that is equipped with a generator for charging the battery as needed, and a device that incorporates predictive power generation and charging control technology. By installing it, it becomes possible to install a small battery and a small generator, and it is possible to reduce fuel consumption without sacrificing the boarding space for buses or the cargo space for trucks, resulting in CO2 reduction. This technology is useful for improving the environment. Furthermore, if applied to a distribution system that supports public transportation and social infrastructure, fuel consumption can be reduced, and at the same time CO2 emissions can be reduced, which can have a great effect on realizing a low-carbon society.

An example of changes in the state of charge (SOC) of the secondary battery depending on the mileage Image diagram that calculates the energy required for movement by acquiring position data and elevation data for each unit section Transition diagram of predictive power generation charging control Flowchart of predictive power generation charging control State where the generator approaches the end point during startup Point to turn off the generator when SOC becomes ScT at the end point (X) Input / output information and processing algorithm of predictive power generation charging control system Relationship between predictive power generation charge control and main blocks Predictive power generation charge control algorithm processing outline Schematic explanatory diagram of predictive power generation charging control (1) Schematic explanatory diagram of predictive power generation charging control (2) Schematic explanatory diagram of predictive power generation charging control (3) Detailed explanatory diagram of predictive power generation charging control Driving route from Tokyo to Numazu SOC status with and without predictive power generation charging control technology

Claims (12)

By setting the destination and / or the traveling route before traveling, the charging start and charging stop points and / or time of the generator during traveling can be set in advance. Predictive power generation and charging control technology for range extender vehicles that charge and drive the motor with the battery. The predictive power generation and charging control technology for a range extender vehicle according to claim 1, wherein the information on the destination and the traveling route utilizes a geographic information system (GIS) and a global positioning satellite system (GNSS). A predictive power generation and charging control technique for a range extender vehicle according to claim 1, characterized in that control is performed when a generator starts charging when a secondary battery charge lower limit value is reached, and when charging stops when a secondary battery charge upper limit value is reached. . According to claim 3, when the traveling condition where the battery consumption is estimated to be high is overestimated, the charging of the generator is started before the lower limit value of the secondary battery is reached, and the battery is regenerated at the traveling destination. Predictive power generation and charging control technology for range extender vehicles, which is characterized by stopping the charging of the generator before reaching the upper limit of the secondary battery by predicting that a large amount of power will be generated. According to claim 3, the remaining battery power required to reach the destination is estimated based on the result of decomposition into energy required to move horizontally to the destination and energy required to move vertically to the destination. Predictive power generation and charging control technology for range extender vehicles, which is characterized by determining from the amount of power lost. According to claim 3, even before and during traveling, based on the information obtained from GIS and GNSS, traveling at the traveling point for each unit distance or unit time, or for each unit combining unit distance and unit time A predictive power generation and charge control technology for range extender vehicles, which incorporates changes in speed, remaining battery power, auxiliary equipment operating status, and installed load capacity to review start or stop of generator charging in real time. A predictive power generation charging control technique for a range extender vehicle according to claim 1, wherein at a point where the generator needs to be stopped on the way of the traveling route, the generator does not operate while passing through the point. A predictive power generation charging control technique for a range extender vehicle according to claim 3, wherein the start and stop of the generator are controlled so that the remaining battery level at the destination becomes a predetermined value. According to claim 8, when it is expected that the remaining battery level at the destination will be less than the predetermined value, the period and traveling place for generating the expected shortage of the amount of electric power will be set to the destination. Predictive power generation and charging control technology for range extender vehicles, which is characterized by being provided in the middle of driving. According to claim 3, when the destination or the driving route is changed in the middle of driving, the information on the changed destination and driving route is obtained from GIS and GNSS again, and the charging of the generator is started. Predictive power generation and charging control technology for range extender vehicles, which is characterized by resetting the stop point or time, or both. A predictive power generation charging control technique for a range extender vehicle according to claim 1, wherein a diesel engine, a gasoline engine, a fuel cell engine, a biomass engine, or the like is used to charge the secondary battery. A predictive power generation charging control technique for a range extender vehicle according to claim 1, further comprising a device capable of charging a secondary battery as needed from a charging facility installed during traveling.